Dengue Hemorrhagic Fever (DHF) is a frequently occurring disease in tropical regions. This is due to the disease vector being the Aedes aegypti mosquito, whose habitat is in tropical environments. Obesity has become a global issue worldwide. Patients with obesity have a stronger immune response due to increased inflammation in circulation. As a result, blood vessels may become wider than usual. This triggers plasma leakage and exacerbates DHF, potentially leading to Severe Dengue Syndrome (SDS). Both of these diseases have various triggering factors such as environmental and productivity-related aspects. In this study, multivariate linear regression analysis will be employed to identify which factors are significant for both diseases. The linear regression analysis will use simultaneous and partial Wilks' Lambda tests. Based on the research findings, it is stated that there are four predictor variables significant for the levels of DHF and obesity, namely, Air Quality Index (), productivity (), poverty rate ( ), and the number of health centers ().
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