Association of Liver Enzyme Levels with Metabolic Syndrome among the Selected Manipuri Population

Introduction: A group of illnesses known as Metabolic Syndrome (MetS) increases the risk of diabetes and cardiovascular disease. Metabolic Syndrome is a serious public health concern. The correlation between MetS and liver enzyme levels has garnered interest, especially among groups experiencing abrupt lifestyle shifts. Aim: This study aims to investigate the relationship between liver enzyme levels and the prevalence of metabolic syndrome among the selected Manipuri population. Materials and Methods: A cross-sectional study was conducted among 300 adults aged 18 years and above in Manipur, India, from January 2022 to June 2022. Participants were recruited through community outreach programs, and individuals with known liver diseases, alcohol dependence, or chronic infections were excluded. Data were collected using structured questionnaires covering demographic information, lifestyle factors, and medical history. Anthropometric measurements and fasting blood samples were obtained for biochemical analyses, including liver enzyme levels (ALT and AST), fasting glucose, and lipid profiles. MetS has been diagnosed according to the International Diabetes Federation Criteria. Statistical analysis was performed using spss version 25.0, with logistic regression models applied to assess associations between liver enzyme levels and mets, adjusting for potential confounders. Results: Out of the 300 participants, 32% were diagnosed with metabolic syndrome. Elevated ALT and AST levels were significantly associated with the presence of metabolic syndrome (p < 0.05). Notably, individuals with higher liver enzyme levels exhibited increased prevalence of abdominal obesity, elevated triglycerides, and insulin resistance. Conclusion: This study highlights a significant association between liver enzyme levels and metabolic syndrome among the Manipur population. The findings suggest that liver function tests could serve as valuable biomarkers for identifying individuals at risk of metabolic disorders, emphasizing the need for targeted public health interventions.