Galoitica: Journal of Mathematical Structures and Applications GJMSA 2834-5568 10.54216/GJSMA https://www.americaspg.com/journals/show/2914 2022 2022 Department of Statistics - College of Administration and Economics -University of Karbala-Iraq Sackineh Sackineh The Spatial Convolution Splines Multivariate Regression Model (SCSMRM) were used on the data represented a diabetes disease measurements across different regions in Iraq (Basrah, Baghdad, Babylon, Sulaimanya) while considering multiple risk factors such as age, BMI, weight , income, education level, blood pressure for the same geographic location  for (200) patient, and  combine the health data with the risk factor data to create a comprehensive dataset. Each record in the dataset should include the geographic location, diabetes status, and values for each risk factor we applied (SCSMRM), the results showed that significant the model and the risk factors studied in the model explain 61% of the changes that occur in the diabetes. It also showed the significance of the factors (age - weight - body mass index (BMI) - educational level - blood pressure) and the non-significance of the variable (income), and these results are consistent with the actual reality of the disease.   2024 2024 66 71 10.54216/GJMSA.0100207 https://www.americaspg.com/articleinfo/33/show/2914