Comparing the Predictive Accuracy of Biochemical and Anthropometric Markers for Metabolic Syndrome in Children with Obesity

Antoine Mircea^*
*Correspondence: Antoine Mircea, Department of Obstetrics and Gynecology, Mbarara University of Science and Technology, P.O. Box 1410 Mbarara, Uganda, Email:

Introduction

Metabolic Syndrome (MetS) is a cluster of metabolic abnormalities, including central obesity, insulin resistance, hypertension, and dyslipidemia, which significantly increases the risk of cardiovascular diseases and type 2 diabetes. In recent years, the rising prevalence of childhood obesity has led to growing concerns regarding early-onset MetS and its long-term health implications. Early detection and intervention are crucial for mitigating these risks, necessitating accurate predictive markers. Biochemical markers, such as fasting glucose, insulin, lipid profiles, and inflammatory cytokines, have been widely studied for their role in diagnosing and predicting MetS. Conversely, anthropometric markers, including Body Mass Index (BMI), Waist Circumference (WC), Waist-To-Height Ratio (WHtR), and skinfold thickness, provide non-invasive and cost-effective means for assessing metabolic risk [1].

Description

Metabolic Syndrome (MetS) is a complex condition characterized by a cluster of interrelated metabolic abnormalities, including central obesity, insulin resistance, hypertension, and dyslipidemia. These risk factors significantly elevate the likelihood of developing type 2 diabetes and cardiovascular diseases later in life. The rising global prevalence of childhood obesity has led to a growing concern regarding early-onset MetS, as children with obesity are at a disproportionately higher risk of developing metabolic complications that persist into adulthood. Early detection and intervention are paramount in mitigating these risks, underscoring the need for reliable and accessible predictive markers. Biochemical markers play a critical role in diagnosing MetS, as they provide direct insights into metabolic dysfunction at a molecular level. Among these markers, fasting blood glucose, insulin levels, lipid profiles (triglycerides, HDL cholesterol), and inflammatory cytokines (such as C-reactive protein and interleukins) are commonly used to assess metabolic health. Insulin resistance, which is a key component of MetS, is frequently evaluated using the Homeostatic Model Assessment of Insulin Resistance (HOMA-IR). Additionally, emerging biomarkers such as adipokines (leptin and adiponectin), liver enzymes, and oxidative stress markers have been increasingly studied for their potential in predicting MetS in children [2].

The advantage of biochemical markers lies in their specificity and ability to detect metabolic dysregulation even before clinical symptoms manifest. However, these tests require invasive blood draws, specialized laboratory analysis, and significant healthcare resources, making them less feasible for routine screening in large populations. On the other hand, anthropometric markers provide a non-invasive, cost-effective, and easily accessible means of assessing metabolic risk. These markers include Body Mass Index (BMI), Waist Circumference (WC), Waist-To-Height Ratio (WHtR), and skinfold thickness measurements, all of which serve as proxies for adiposity and fat distribution. BMI has been widely used as a general measure of obesity; however, it does not differentiate between lean mass and fat mass, nor does it capture fat distribution, which plays a crucial role in metabolic risk. WC and WHtR have been increasingly recognized as better indicators of central obesity, a major driver of insulin resistance and metabolic dysfunction. Studies have shown that WHtR, in particular, may have superior predictive value for MetS compared to BMI, as it accounts for variations in height and provides a more accurate assessment of visceral fat accumulation. Additionally, newer imaging techniques such as Dual-Energy X-Ray Absorptiometry (DXA) and Bioelectrical Impedance Analysis (BIA) offer more precise body composition assessments but are less commonly used due to cost and availability constraints [3].

A key aspect of comparing biochemical and anthropometric markers is evaluating their predictive accuracy in identifying MetS in children with obesity. Several studies have attempted to establish cutoff values for various markers, aiming to optimize sensitivity and specificity. While biochemical markers generally exhibit higher specificity, anthropometric markers offer greater practicality for large-scale screenings. Combining both types of markers may provide an optimal strategy, allowing for initial identification using anthropometric measures followed by confirmation through biochemical analysis. Additionally, recent advancements in machine learning and predictive modeling have enabled the integration of multiple biomarkers to enhance diagnostic accuracy and risk stratification. holds the potential to enhance early identification, enabling timely interventions to reduce the long-term burden of metabolic disorders. This study aims to compare the predictive accuracy of biochemical and anthropometric markers for MetS in children with obesity, evaluating their utility in clinical and public health settings. An integrated approach combining both marker types, alongside advancements in predictive modeling [4].

Despite the growing body of research, several challenges remain in standardizing predictive markers for MetS in children. Variability in diagnostic criteria across different populations, ethnic differences in fat distribution and metabolic responses, and the impact of pubertal changes on metabolic parameters all contribute to inconsistencies in defining and identifying MetS in pediatric cohorts. Future research should focus on longitudinal studies to track the progression of MetS from childhood to adulthood, refining predictive models to enhance early detection and intervention strategies. Moreover, public health initiatives should aim to improve accessibility to metabolic screening and preventive healthcare services, particularly in underserved populations. In conclusion, both biochemical and anthropometric markers play crucial roles in predicting MetS in children with obesity, each with its own advantages and limitations. While biochemical markers provide precise metabolic insights, their invasive nature and resource requirements pose challenges for routine use. Anthropometric markers offer a practical alternative for large-scale screenings but may lack specificity in certain cases [5].

Conclusion

The findings of this study highlight the comparative strengths and limitations of biochemical and anthropometric markers in predicting MetS in children with obesity. While biochemical markers offer precise metabolic insights and reflect physiological dysfunction at a molecular level, they require invasive procedures and laboratory analysis, limiting their feasibility in routine screening. Anthropometric markers, on the other hand, provide accessible and cost-effective screening tools that correlate well with metabolic risk factors. However, their predictive accuracy varies across populations and requires standardization for optimal use. Ultimately, an integrated approach combining both marker types may offer the most effective strategy for early identification and intervention. Future research should focus on refining predictive models by incorporating novel biomarkers and machine learning techniques to enhance accuracy and applicability in diverse pediatric populations.

Acknowledgement

None.

Conflict of Interest

None.

References

1.  Sebastian, Emilia Odyjewska, Artur Bossowski and Barbarka-Olszewska. "Not only metabolic complications of childhood obesity." Nutrients 16 (2024): 539.

 Google Scholar Cross Ref Indexed at

2. Ho, Howard Chong Huat, Ernesto Maddaloni and Raffaella Buzzetti. "Risk factors and predictive biomarkers of early cardiovascular disease in obese youth." Diabetes Metab Res Rev 35 (2019): e3134.

Google Scholar Cross Ref Indexed at

3. Bijari, Moniba, Sara Jangjoo, Nima Emami and Sara Raji, et al. "The Accuracy of Visceral Adiposity Index for the Screening of Metabolic Syndrome: A Systematic Review and Meta�" Int J Endocrinol 2021 (2021): 6684627.

 Google Scholar Cross Ref Indexed at

4. Wasniewska, Malgorzata, Giorgia Pepe, Tommaso Aversa and Simonetta Bellone, et al. "Skeptical look at the clinical implication of metabolic syndrome in childhood obesity." Children 10 (2023): 735.

 Google Scholar Cross Ref Indexed at

5. Aydin, Banu Kucukemre, Rasmus Stenlid, Iris Ciba and Sara Y. Cerenius, et al. "High levels of FSH before puberty are associated with increased risk of metabolic syndrome during pubertal transition." Pediatric Obesity 17 (2022): e12906.

 Google Scholar Cross Ref Indexed at