Financial Burden of Weight Gain: A Secondary Analysis Study on MNGHA’s Employees, Saudi Arabia

Seham Khashwayn; Rouza Alnoaimi; Amina Alaqal; Amal Hasan

doi:10.56338/ijhess.v7i2.7089

Seham Khashwayn Research Office, King Abdullah International Medical Research Center, Alhasa, KSA. Research, King Saud Bin Abdulaziz University for Health Sciences, Alhasa, KSA. College of Business Administrator, University of Bahrain, Zallaq, Kingdom of Bahrain
Rouza Alnoaimi College of Business Administrator, University of Bahrain, Zallaq, Kingdom of Bahrain
Amina Alaqal College of Business Administrator, University of Bahrain, Zallaq, Kingdom of Bahrain. Information and E-government Authority, Manama, Kingdom of Bahrain
Amal Hasan College of Business Administrator, University of Bahrain, Zallaq, Kingdom of Bahrain

DOI: https://doi.org/10.56338/ijhess.v7i2.7089

Keywords: Obesity, Machine Learning, Employee Health, Financial Burden, Healthcare Cost

Abstract

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.

References

Goettler, A., Grosse, A., & Sonntag, D. (2017). Productivity loss due to overweight and obesity: a systematic review of indirect costs. BMJ open, 7(10), e014632.

Jaoua, N., Woodman, A., and Withers, M. (2020). Predictors of Overweight and Obesity Among Employees of Sadara Chemical Company in the Kingdom of Saudi Arabia. Obesity Medicine, 18, 100198.

Malkin, J. D., Baid, D., Alsukait, R. F., Alghaith, T., Alluhidan, M., Alabdulkarim, H., et al. (2022). The Economic Burden of Overweight and Obesity in Saudi Arabia. PLoS ONE, 17(3), e0264993.

Risks. (2022). Modeling the Economic Cost of Obesity Risk and Its Relation to the Body Mass Index. Risks, 10(10), 197.

Dobbs, R., Sawers, C., Thompson, F., Manyika, J., Woetzel, J., Child, P., ... & Spatharou, A. (2021). Economic impacts of overweight and obesity: current and future estimates for eight countries. BMJ Global Health, 6(10), e006351.

Wang, Y. C., McPherson, K., Marsh, T., Gortmaker, S. L., & Brown, M. (2011). Health and Economic Burden of the Projected Obesity Trends in the USA and the UK. The Lancet, 378(9793), 815–825.

Jensen, M. D., Ryan, D. H., Apovian, C. M., et al. (2014). 2013 AHA/ACC/TOS Guideline for the Management of Overweight and Obesity in Adults. Circulation, 129(25_suppl_2), S102–S138.

Tsai, A. G., Williamson, D. F., & Glick, H. A. (2011). Direct Medical Cost of Overweight and Obesity in the USA: A Quantitative Systematic Review. Obesity Reviews, 12(1), 50–61.

Hammond, R. A., & Levine, R. (2010). The Economic Impact of Obesity in the United States. Diabetes, Metabolic Syndrome and Obesity: Targets and Therapy, 3, 285–295.

Bhoir, M., & Sinha, V. (2024). Employee well-being human resource practices: A systematic literature review and directions for future research. Future Business Journal, 10, Article number: 95. https://doi.org/10.1186/s43093-024-00382-w Benchmarking Study. Journal of Occupational and Environmental Medicine, 49(2), 111–130.

Khashwayn, S., Alqahtani, M. B., Al Katheer, S. A., Al Hussaini, A. A., Bakhashwayn, M. A., & Al Qarni, A. A. (2024). The Prevalence of Weight Gain After Obtaining Employment: A Cross-Sectional Survey of Employees at the Ministry of National Guard Health Affairs, Eastern Region, Saudi Arabia. Cureus, 16(3), e56572.

Alqahtani, S. A., Al-Omar, H. A., Alshehri, A., & Others. (2023). Obesity Burden and Impact of Weight Loss in Saudi Arabia: A Modelling Study. Advances in Therapy,40,1114–1128.

Cawley, J., & Meyerhoefer, C. (2012). The Medical Care Costs of Obesity: An Instrumental Variables Approach. Journal of Health Economics, 31(1), 219–230.

van den Broek-Altenburg, E., Atherly, A., & Holladay, E. (2022). Changes in healthcare spending attributable to obesity and overweight: payer- and service-specific estimates. BMC Public Health, 22, Article number:962.

Van Drongelen, A., Boot, C. R., Hlobil, H., van der Beek, A. J., & Smid, T. (2011). Cumulative Exposure to Shift Work and Obesity: Current Evidence and Limitations. Scandinavian Journal of Work, Environment & Health, 37(4), 263–275.

Song, G., Dong, X., Wu, J., & Wang, Y.-G. (2017). Blockwise AICc for model selection in generalized linear models. Environmental Modeling & Assessment, 22(5), 523–533.

Financial Burden of Weight Gain: A Secondary Analysis Study on MNGHA’s Employees, Saudi Arabia

Abstract

References

Instruction for Author