<![CDATA[Introduction: Obesity and related chronic health conditions pose significant financial and healthcare implications in workplace settings worldwide. The objective of this study is to examine the economic impact of weight gain among full-time employees working at the Ministry of National Guard Health Affairs (MNGHA) in Alhasa and Dammam, Saudi Arabia. Methods: In order to achieve the research objective a drawing from cross-sectional datasets, the research was done to estimate the healthcare costs associated with each additional kilogram of weight gain and to explore its link to the occurrence of chronic illnesses such as Type 2 Diabetes, Hypertension, Asthma, and Depression. Traditional and machine learning models were used to estimate the approximate cost of weight gain per kilogram. The models include Linear, KNN, Random Forest, Decision Tree, Linear SVM, and RBF SVM applied on both SAS 9.4 and Python. Models were evaluated to select the most suitable model. Results: Hypothesis testing and correlation showed a significant difference between work schedules, age, and year of experience. The model estimated that with every one-kilogram gain in weight, the total burden increases by 676 SAR. Conclusion: This study clearly showed that incremental weight gain among MNGHA employees contributes to a significant financial burden on healthcare costs.]]>
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