A Novel Metabolic Risk Classification System Incorporating Body Fat, Waist Circumference, and Muscle Strength

• Published in: Journal of functional morphology and kinesiology Vol. 10; no. 1; p. 72
• Main Authors: Robledo-Millán, Carlos Raúl, Diaz-Domínguez, María Regina, Castañeda-Ramírez, Ari Evelyn, Quiñones-Lara, Efrén, Valencia-Marín, Sebastián, Suárez-García, Ricardo Xopán, López-Desiderio, Nely Gisela, Ramos-Cortés, Claudio Adrían, Gaytán Gómez, Areli Marlene, Bello-López, Juan Manuel, Saldívar-Cerón, Héctor Iván
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 22.02.2025; MDPI
• Subjects: Blood cholesterol; Blood pressure; Body composition; Body fat; Body mass index; Chi-square test; Cholesterol; Data collection; Diabetes; Fasting; Females; Glucose; grip strength; High density lipoprotein; Medical records; Metabolic disorders; metabolic risk; Metabolic syndrome; Muscle strength; obesity; Physiological aspects; public health; Risk assessment; Risk factors; risk stratification; Sarcopenia; Triglycerides; Type 2 diabetes; Mexico; United States > US; Germany; metabolic syndrome; body composition; risk stratification; grip strength; metabolic risk; obesity; public health
• ISSN: 2411-5142; 2411-5142
• DOI: 10.3390/jfmk10010072

Background: As metabolic diseases continue to rise globally, there is a growing need to improve risk assessment strategies beyond traditional measures such as BMI and waist circumference, which may fail to identify individuals at risk. This study develops and validates a novel metabolic risk classification system that incorporates body fat percentage (%BF), waist circumference (WC), and grip strength (GS) in Mexican adults. It aims to improve risk stratification and evaluate the association with metabolic syndrome. Methods: This cross-sectional study involved 300 young adults (18–22 years) from a university in Mexico City, utilizing body composition (%BF) and anthropometric measures (WC, GS) to categorize them into four risk groups: protective, low risk, increased risk, and high risk. A retrospective cohort of 166 adults (18–65 years) with complete clinical records was used for validation. Results: The inclusion of GS in the risk assessment significantly shifted the distribution in the young adult cohort, reducing the “no risk” category (15.5% males, 11.6% females) and expanding the higher-risk categories (70.2% males, 69% females). Metabolic parameters such as fasting glucose, triglycerides, HDL cholesterol, and blood pressure worsened progressively across the risk categories (p < 0.001). The high-risk group exhibited a markedly increased odds ratio for metabolic syndrome at 28.23 (10.83–73.6, p < 0.001), with no cases in the protective and low-risk groups. Conclusions: Integrating grip strength with %BF and WC into a risk classification system substantially enhances metabolic risk stratification, identifies at-risk individuals not previously detected, and confirms a protective group. This validated system provides a robust tool for early detection and targeted interventions, improving public health outcomes in metabolic health.