Children with “metabolically healthy obesity” (MHO) are a distinct subgroup of youth with obesity, who are less prone to the clustering of cardiometabolic risk factors. Although this phenotype, frequently defined by the absence of metabolic syndrome components or insulin resistance, was first described during the early 1980s, a consensus-based definition of pediatric MHO was introduced only recently, in 2018. The purpose of this review was to concisely summarize current knowledge regarding the MHO phenomenon in youth. The prevalence of MHO in children varies from 3 to 87%, depending on the definition used and the parameters evaluated, as well as the ethnicity and the pubertal status of the sample. The most consistent predictors of MHO in youth include younger age, lower body mass index, lower waist circumference, and lower body fat measurements. Various hypotheses have been proposed to elucidate the underlying factors maintaining the favorable MHO phenotype. While preserved insulin sensitivity and lack of inflammation were previously considered to be the main etiological factors, the most recent findings have implicated adipokine levels, the number of inflammatory immune cells in the adipose tissue, and the reduction of visceral adiposity due to adipose tissue expandability. Physical activity and genetic factors also contribute to the MHO phenotype. Obesity constitutes a continuum-increased risk for cardiometabolic complications, which is less evident in children with MHO. However, some findings have highlighted the emergence of hepatic steatosis, increased carotid intima-media thickness and inflammatory biomarkers in the MHO group compared to peers without obesity. Screening should be directed at those more likely to develop clustering of cardiometabolic risk factors. Lifestyle modifications should include behavioral changes focusing on sleep duration, screen time, diet, physical activity, and tobacco smoke exposure. Weight loss has also been associated with the improvement of insulin sensitivity and inflammation. Further investigative efforts are needed in order to elucidate the mechanisms which protect against the clustering of cardiometabolic risk factors in pediatric obesity, to provide more efficient, targeted treatment approaches for children with obesity, and to identify the protective factors preserving the MHO profile, avoiding the crossover of MHO to the phenotype with metabolically unhealthy obesity.

To evaluate siMS score and siMS risk score, novel continuous metabolic syndrome scores as methods for quantification of metabolic status and risk. Developed siMS score was calculated using formula: siMS score = 2*Waist/Height + Gly/5.6 + Tg/1.7 + TA_systolic/130—HDL/1.02 or 1.28 (for male or female subjects, respectively). siMS risk score was calculated using formula: siMS risk score = siMS score * age/45 or 50 (for male or female subjects, respectively) * family history of cardio/cerebro-vascular events (event = 1.2, no event = 1). A sample of 528 obese and non-obese participants was used to validate siMS score and siMS risk score. Scores calculated as sum of z-scores (each component of metabolic syndrome regressed with age and gender) and sum of scores derived from principal component analysis (PCA) were used for evaluation of siMS score. Variants were made by replacing glucose with HOMA in calculations. Framingham score was used for evaluation of siMS risk score. Correlation between siMS score with sum of z-scores and weighted sum of factors of PCA was high (r = 0.866 and r = 0.822, respectively). Correlation between siMS risk score and log transformed Framingham score was medium to high for age groups 18+,30+ and 35+ (0.835, 0.707 and 0.667, respectively). siMS score and siMS risk score showed high correlation with more complex scores. Demonstrated accuracy together with superior simplicity and the ability to evaluate and follow-up individual patients makes siMS and siMS risk scores very convenient for use in clinical practice and research as well.

Although there are substantial data linking thyroid autoimmunity (TAI) and infertility, data regarding assisted reproductive technology (ART) outcomes and TAI markers in follicular fluid (FF) of women undergoing ART are scarce. Objective of the study was to assess the association of the levels of thyroid autoantibodies in FF and ART outcome expressed as the achieved pregnancies. This study enrolled 52 women undergoing ART (26 TAI positive subjects and 26 age and body mass index matched TAI negative controls). Blood samples were drawn before the initiation of protocol for controlled ovarian stimulation, and thyrotropin (TSH), free triiodothyronine (fT₃), free thyroxine (fT₄), thyroid peroxidase antibodies (TPOAbs) and thyroglobulin antibodies (TgAbs) levels were measured. TSH, fT₄, TPOAbs, TgAbs and progesterone levels were also measured in FF. There were no significant differences between the groups regarding mean levels of FF TSH and FF fT₄. Statistically significant correlation was discovered regarding the levels of serum and FF TPOAbs (0,961, p<0.001 in TAI positive, 0,438, p = 0.025 in TAI negative group) and TgAbs (0,945, p<0.001 in TAI positive, 0,554, p = 0.003 in TAI negative group). Pregnancies rates per initiated cycle and per embryotransfer cycle were significantly different between TAI positive and TAI negative group, (30.8% vs 61.5%), p = 0.026 and (34.8% vs 66.7%), p = 0.029, respectively. Multivariate analysis showed that TAI positive women had less chance to achieve pregnancy (p = 0.004, OR = 0.036, 95% CI 0.004–0.347). Higher levels of thyroid autoantibodies in FF of TAI positive women are strongly correlated with serum levels and may have effect on the post-implantation embryo development.