Evaluation of Anthropometric Measurements and BiochemicalParameters in Individuals Diagnosed with Schizophrenia. Master's Thesis,

In this study, metabolic health indicators (e.g., fasting blood glucose, lipid profile, body mass index, etc.) in individuals diagnosed with schizophrenia were examined, and the variations in these indicators based on factors such as gender, education level, and employment status were evaluated. The study was designed as a retrospective, descriptive, and cross-sectional research. It included 178 schizophrenia patients whose records were available at the Psychiatry Department of Niğde Ömer Halis Demir University Training and Research Hospital between September 2022 and September 2023. Data were retrospectively collected from patient files. Demographic and clinical information was obtained through the Patient Information Form, anthropometric measurements included Waist Circumference (WC) and Body Mass Index (BMI), and biochemical data, such as Fasting Blood Glucose (FBG), Low-Density Lipoprotein Cholesterol (LDL-K), High-Density Lipoprotein Cholesterol (HDL-K), and Triglycerides (TG), were gathered using the Biochemical Parameters Information Form. The data were analyzed using IBM SPSS 25.0 software through descriptive statistics, correlation analyses, and Chi-square tests. The findings revealed that women had higher WC and BMI values compared to men, while men exhibited more pronounced lipid profile abnormalities. The mean FBG was determined to be 111.22 mg/dL, indicating a significant risk factor for diabetes. Individuals with lower education levels were found to have higher metabolic health risks and limited awareness of healthy eating. Unemployed individuals were observed to have elevated LDL-K and TG levels. Metabolic health profile abnormalities were associated with the metabolic side effects of antipsychotic medications, unhealthy dietary habits, and sedentary lifestyles.The study concluded that metabolic health indicators in individuals diagnosed with schizophrenia vary according to factors such as gender, education level, and employment status. To reduce metabolic health risks in this population, personalized nutritional interventions, regular physical activity, and awareness training are recommended.