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Abstract Body mass index (BMI) is a well-known risk factor for type 2 diabetes mellitus (T2DM). We aimed to identify BMI trajectory patterns and evaluate their association with T2DM during 18 years of follow-up. We included 6026 participants aged 20 to 65 from the prospective population-based Tehran Lipid and Glucose Study (TLGS). The BMI trajectory patterns were identified using latent growth mixture modeling (LGMM) during the measurement period. The association between the BMI trajectory patterns and future T2DM was evaluated using the Cox proportional hazard regression models. Three BMI trajectory patterns of low-increasing (38.6%), medium-increasing (47.1%), and high-increasing (14.3%) were detected. The participants in the medium-increasing and high-increasing BMI trajectory groups had HRs of 1.87 (95% CI 1.53–2.28) and 3.41(95% CI 2.71–4.29) for T2DM incidence, respectively. Within the normoglycemic subpopulation, the high-increasing BMI group had an HR of 3.82 (95% CI 2.79–5.24) compared to the low-increasing BMI group, while in the prediabetic subpopulation, the high-increasing BMI group had an HR of 2.93 (95% CI 2.04–4.19) compared to the low-increasing BMI group. Body weight varies in a relatively stable pattern in adulthood over the long-term period. Medium and high-increasing BMI trajectory patterns have a significantly increased risk for future T2DM in both normoglycemic and prediabetic individuals. Identifying BMI trajectory patterns can help healthcare providers in early prediction, risk assessment, and monitoring strategies development for the prevention of T2DM.

Abstract Type 2 diabetes and thyroid function disorders are two common chronic endocrine disorders with the high prevalence in various populations. Metformin is well established as the first-line drug therapy for managing diabetes mellitus. In this meta-analysis, we aimed to determine the effect of metformin on serum TSH and FT4 concentrations in patients with type 2 diabetes. We searched PubMed, Scopus, web of science, Cochrane library, and google scholar to collect information on the effect of metformin on serum TSH and FT4 levels. Demographic and clinical information and serum TSH and FT4 concentrations before and after metformin treatment were extracted. Studies on patients over 18 years of age were included. A total of 11 studies including 1147 patients were selected for the final analysis. In hypothyroid patients, the TSH level decreased significantly after treatment with metformin (Hedges’s g:1.55, 95%CI 0.93–2.16, p-value

Abstract Traditional metabolic syndrome (MetS) criteria have several limitations, which hinder its use in clinical practice. To overcome the limitations, we investigated the association between age- and sex-specific continuous MetS severity score (cMetS-S) and cardiovascular disease (CVD) and mortality beyond MetS components in the framework of the Tehran Lipid and Glucose Study. Participants aged 20–60 years at baseline were included in the study. We excluded participants with CVD, cancer, use of corticosteroids, estimated glomerular filtration rate

Abstract 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.

Abstract Previous epidemiologic studies debated the association of body mass index (BMI) trends with cardiovascular disease and mortality. This study aimed to evaluate the association of BMI variability and slope with the incidence of Type 2 diabetes mellitus (T2DM) in a sex-stratified 15.8-year follow-up in the population-based Tehran Lipid and Glucose Study (TLGS). Of 10,911 individuals aged 20–60 years, 4981 subjects were included and followed for 15.8-years. The slope coefficient of BMI in the linear regression model represented individuals’ BMI trends up to the incidence of DM. The root mean squared error (RMSE) of the BMI linear trend was selected to reflect BMI variability through six follow-ups. Cox proportional hazards regression was used to investigate the association of the baseline BMI, BMI slope and RMSE with the incidence of T2DM among men and women. Multivariable-adjusted HRs of T2DM for each SD increment in BMI slope was 1.18 (95% CI: 0.94–1.48, p = 0.161) in normal weight men and 1.26 (95% CI: 1.10–1.44, p = 0.001) in overweight and obese men. However, in women, each SD increment in BMI slope increased the risk of T2DM with a HR of 1.19 (95% CI: 1.01–1.40, p = 0.039) in normal weight, and 1.14 (95% CI: 1.08–1.19, p