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Metabolic syndrome (MetS), defined as the coexistence of interrelated cardiometabolic risk factors, is limited by ignoring the severity of the disease and individuals with a pre-metabolic state. We aimed to develop the first age- and sex-specific continuous MetS severity score in the adult population using confirmatory factor analysis (CFA) based on the MetS components in the Middle East. Using data from the population-based Tehran Lipid and Glucose Study (TLGS) I and II datasets, we conducted CFA of the single factor MetS on 8933 adults (20–60 years old) totally, and in age and sex subgroups. We allowed for different factor loadings across the subgroups to formulate age- and sex-specific continuous MetS severity score equations. Thereafter, we validated these equations in the dataset of TLGS III participants. Triglyceride had the highest factor loading across age and sex subgroups, indicating the most correlation with MetS. Except for women aged 40–60 years, waist circumference was the second most significant factor contributing to MetS. Systolic blood pressure was more closely related to MetS in women than in men. Systolic blood pressure and fasting plasma glucose had the weakest correlation with MetS among the 40–60 age group. Moreover, as women age, the contribution of fasting plasma glucose to MetS tended to decline, while it remained relatively constant in men. The resulting MetS severity score was correlated with age and homeostasis model assessment of insulin resistance. Furthermore, the continuous MetS severity score well predicted the traditional MetS according to receiver operating characteristic analysis in the validation dataset. The age- and sex-specific continuous MetS severity score for the West Asian adult population provides a tangible quantitative measure of MetS enabling clinicians to screen and monitor the individuals at risk and assess their metabolic trends.

Objective To investigate the association between the dynamic course of insulin resistance and chronic kidney disease (CKD). Methods In a longitudinal population-based Tehran Lipid and Glucose Study, 3071 eligible participants aged ≥20 years were followed for 18 years at three-year intervals. HOMA-IR and clinical surrogate markers of insulin resistance, including triglyceride-glucose index (TyG), visceral adiposity index (VAI), and lipid accumulation product (LAP), were calculated. Using latent variable mixture modeling, sex-specific trajectories were plotted for each insulin resistance marker. Trajectory group association of the insulin resistance markers with CKD was determined using the multivariate cox proportional hazards regression model. Results For HOMA-IR, two distinct trajectory patterns (stable and increasing), and for TyG, VAI, and LAP, three trajectories (low, moderate, high) were identified. The participants with increasing HOMA-IR trajectory had a significantly increased risk of CKD in men (HR: 1.72, 95%CI: 1.06-2.79) and women (HR: 1.37, 95%CI: 1.00-1.89) after adjusting confounding variables. The high TyG and VAI trajectory classes were associated with a higher risk of CKD than the low TyG and VAI trajectory classes in both men (TyG: HR:1.97, 95%CI: 1.12-3.46; VAI: HR:1.66, 95%CI:1.06-2.62) and women (TyG: HR:1.50, 95%CI:1.06-2.12; VAI: HR:1.66, 95%CI:1.20-2.31). In contrast, the High LAP (HR: 3.38, 95%CI: 2.08-5.48) trajectory was associated with incident CKD only in women. Conclusion An increasing trend of HOMA-IR is associated with a higher risk of CKD in men and women. Among clinical insulin resistance surrogate markers, abnormal trajectory patterns of LAP in women and TyG and VAI in both sexes are associated with a higher risk of CKD.