Recent evidence shows that simple and inexpensive anthropometric measurements can be used to identify, at an early stage, women with obesity at increased risk of developing metabolic syndrome (MetS). Thus, the aim of this study was to compare the accuracy of five different indexes of adiposity and/or body composition in identifying MetS in a group of 876 women (mean age ± SD: 52.1 ± 13.8 years; body mass index (BMI): 43.6 ± 6.1 kg m⁻²). The following indexes were determined for each subject: waist-to-hip ratio (WHR), waist-to-height ratio (WtHR), body mass fat index (BMFI), visceral adiposity index (VAI), and cardiometabolic index (CMI). Overall, the presence of MetS was detected in 544 patients (62%). Pearson correlation coefficients were calculated to evaluate the relationships between body composition indexes and metabolic characteristics of the women. Receiver operating characteristic (ROC) analysis was used to determine the best predictor for each adiposity index among metabolic risk factors. The ROC analysis showed VAI (AUC = 0.84) and CMI (AUC = 0.86) showed the best performance in predicting MetS. Differences were found between the ROC area of CMI and VAI with all other indexes (p < 0.05). The optimal cutoff point for early diagnosis of MetS was >0.92 for WHR, >0.76 for WtHR, >30.1 kg m⁻¹ for BMFI, >1.94 for VAI, and >0.84 for CMI. In addition, VAI and CMI were the most sensitive and specific indexes compared with other indexes. In conclusion, VAI and CMI represent the most useful and reliable indexes to be used for detecting MetS in women suffering from obesity in clinical practice.

Background: Metabolic syndrome (MetS) is a globally increasing pathological condition. Recent research highlighted the utility of complete blood count-derived (CBC) inflammation indexes to predict MetS in adults with obesity. Methods: This study examined CBC-derived inflammation indexes (NHR, LHR, MHR, PHR, SIRI, AISI, and SII) in 231 adults with severe obesity (88 males, 143 females; age: 52.3 [36.4–63.3] years), divided based on the presence (MetS+) or absence (MetS-) of MetS. The relationships between the indexes and the cardiometabolic risk biomarkers HOMA-IR, TG/HDL-C, and non-HDL-C were also evaluated. Results: Individuals with metabolic syndrome (MetS+) had significantly higher values of MHR, LHR, NHR, PHR, and SIRI than those without (MetS-) (MHR and NHR: p < 0.0001; LHR: p = 0.001; PHR: p = 0.011; SIRI: p = 0.021). These values were positively correlated with the degree of MetS severity. Logistic regression (MHR and NHR: p = 0.000; LHR: p = 0.002; PHR: p = 0.022; SIRI: p = 0.040) and ROC analysis (MHR: AUC = 0.6604; LHR: AUC = 0.6343; NHR: AUC = 0.6741; PHR: AUC = 0.6054; SIRI: AUC = 0.5955) confirmed the predictive potential of CBC-derived inflammation indexes for MetS in individuals with severe obesity. CBC-derived inflammation indexes also correlated with HOMA-IR (MHR, LHR, and NHR: p < 0.0001; PHR: p < 0.001; SIRI: p = 0.000) and TG/HDL-C (MHR, LHR, NHR and PHR: p < 0.0001; SIRI: p = 0.006). Conclusions: In conclusion, this study validates CBC-derived inflammation indexes for predicting MetS in individuals with severe obesity. The relationships between these indexes and cardiometabolic risk factors can enable clinicians to better grade MetS associated with obesity.

Metabolic syndrome (MetS) associated with obesity is a pathological condition increasing worldwide. Recent studies have demonstrated that the neutrophil to lymphocyte ratio (NLR) can be successfully used to stage MetS in obese adults. The aim of the study was to evaluate NLR values in 552 children/adolescents (M 219, F 333; 14.8 [12.9–16.3] years) and 231 adults (M 88, F 143; 52.3 [36.4–63.3] years) with morbid obesity, subdivided into subgroups according with the presence or absence of MetS. Adult patients with obesity showed a higher prevalence of MetS compared to the pediatric population (71% vs 26%), associated with a greater number of subjects with 3 and 4–5 altered components for MetS. NLR was higher (P-value = 0.041) in adults with MetS compared with those without. NLR values also positively correlated with the severity grade of the syndrome (P-value = 0.032). By contrast, in pediatric subjects with obesity with MetS, NLR values were comparable with those recorded in subjects without MetS (P-value = 0.861), no correlation being found with MetS severity (P-value = 0.441). Our study confirms the importance of NLR as an inflammatory indicator associated with MetS in adult subjects with severe obesity, while it excludes a similar role in children/adolescents.

Background: Childhood obesity is a globally increasing pathological condition leading to long-term health issues such as cardiovascular diseases and metabolic syndrome (MetS). This study aimed to determine the clinical value of the Complete Blood Count-derived inflammation indexes Monocyte/HDL-C ratio (MHR), Lymphocyte/HDL-C ratio (LHR), Neutrophil/HDL-C ratio (NHR), and System Inflammation Response Index (SIRI) to predict the presence of metabolic syndrome and its association with cardiovascular risk markers (HOMA-IR, TG/HDL-C, and non-HDL-C) in children and adolescents with obesity. Methods: The study included a total of 552 children/adolescents with severe obesity (BMI: 36.4 [32.7–40.7] kg/m²; 219 males, 333 females; age: 14.8 [12.9−16.3] years), who were further subdivided based on the presence or absence of metabolic syndrome (MetS+ and MetS respectively). Results: The MHR, LHR, and NHR indexes (p < 0.0001), but not SIRI (p = 0.524), were significantly higher in the MetS+ compared to the MetS− subgroup, showing a positive correlation with the degree of MetS severity (p < 0.0001). Furthermore, MHR, LHR, and NHR were positively associated with cardiometabolic risk biomarkers (HOMA-IR: MHR p = 0.000, LHR p = 0.001, NHR p < 0.0001; TG/HDL-C: MHR, LHR, NHR p < 0.000; non-HDL-C: MHR, LHR p < 0.0001, NHR p = 0.000). Finally, the ROC curve analysis demonstrated that among the analyzed indexes, only MHR, LHR, and NHR had diagnostic value in distinguishing MetS patients among children and adolescents with obesity (MHR: AUC = 0.7045; LHR: AUC = 0.7205; NHR: AUC = 0.6934; p < 0.0001). Conclusions: In conclusion, the MHR, LHR, and NHR indexes, but not the SIRI index, can be considered useful tools for pediatricians to assess the risk of MetS and cardiometabolic diseases in children and adolescents with obesity and to develop multidisciplinary intervention strategies to counteract the widespread disease.