DOI: https://doi.org/10.36347/sjmcr.2026.v14i03.009

Pages: 352-358

Background: Obesity and metabolic syndrome are major public health challenges worldwide and are associated with increased cardiovascular risk and type 2 diabetes. Lifestyle interventions remain the cornerstone of prevention and management. The Mediterranean diet has consistently been associated with improved cardiometabolic outcomes; however, translating evidence into effective counseling strategies in routine practice remains challenging. Objective: To summarize current evidence on Mediterranean diet counseling in adults with obesity and/or metabolic syndrome and to highlight practical implications for clinical practice and public health interventions. Methods: We conducted a narrative review of published studies addressing Mediterranean diet interventions, counseling strategies, adherence determinants, and cardiometabolic outcomes in adults. Evidence was synthesized to provide a practical overview for clinicians and multidisciplinary teams involved in lifestyle management. Results: Mediterranean diet counseling is associated with improvements in body weight, waist circumference, lipid profile, glycemic control, inflammatory markers, and overall cardiometabolic risk. Effective counseling strategies commonly include individualized nutritional education, goal setting, motivational interviewing, culturally adapted dietary plans, and structured follow-up. Barriers to adherence include socioeconomic constraints, limited access to healthy foods, low health literacy, and competing lifestyle priorities. Multidisciplinary approaches and community-based programs may enhance long-term adherence. Conclusion: Mediterranean diet counseling represents a feasible and evidence-based strategy for improving cardiometabolic health in adults with obesity and metabolic syndrome. Integrating structured counseling methods, culturally appropriate educational tools, and coordinated multidisciplinary care may optimize adherence and outcomes. Further research is needed to identify scalable m