Year: 2026 | Month: October | Volume: 16 | Issue: 10 | Pages: 152-159
DOI: https://doi.org/10.52403/ijhsr.20261016
Association of Biomarkers in Metabolic Diseases: Early Prediction of Risk Factors for Cardiovascular Diseases Risk
S. Ramya1, Aswathy Anil2
1Associate Professor, Department of Physiology, Sri Lalithambigai Medical College and Hospital, Dr MGR Educational University and Research Institute, Maduravoyal, Chennai 95, India
2Associate Professor, Department of Physiology, Sri Lalithambigai Medical College and Hospital, Dr MGR Educational University and Research Institute, Maduravoyal, Chennai, India
Corresponding Author: Dr S. Ramya
ABSTRACT
Background: Depending on the mode of presentation, CVD increases death rates by three to seven times. Serum total cholesterol is a strong predictor of the risk of CV events in people with diabetes. Mortality and morbidity are significantly increased with duration. It is crucial to evaluate the significant risk factors in diabetes.
Methodology: It is a cross-sectional study and comprised of 140 subjects. Demographic details and Blood samples for biochemical parameters of the subjects were collected and recorded. Participants who met the inclusion criteria were divided in to three groups and evaluated the cardiovascular risk markers such as, RDW, TLC, NLR, HsCRP and GGT in metabolic diseases patients,
Results: Group A subjects have shown significant (p<0.005, p<0.003) and positive correlation with NLR. In group B it was found that TLC was statistically significant and positive correlation with DBP. In Group C Subjects with T2DM, obesity, Hypertension and Dyslipidemia, TLC has shown significance (p<0.024) and inverse correlation with SBP and NLR was found to be statistically significant (p<0.042) and inversely correlated with HbA1C.
Discussion: In our study, it was established that one of the metabolic components in all subdivided groups shows significance and positive correlation with TLC and NLR. T2DM subjects have shown significant (p<0.005, p<0.003) and positive correlation with NLR Subjects with T2DM, obesity, Hypertension and Dyslipidemia, TLC has shown significance (p<0.024) and inverse correlation with SBP and NLR was found to be statistically significant (p<0.042) and inversely correlated with HbA1C.
Conclusion: Thus, knowing the principle of Metabolic diseases not only provides a practical and effective technique to identify individuals with multiple risk factors for cardiovascular diseases, but also provides insight to public health policy planners for future prevention and promotion of healthy living. Finally, patients with metabolic diseases need to face financial strain and it becomes the burden for the developing society.
Key words: Metabolic diseases. cardio vascular diseases, Biomarkers