EN
Optimal control of diabetes model with the impact of endocrine-disrupting chemical: an emerging increased diabetes risk factor
Abstract
Diabetes, a persistent pathological condition characterized by disruptions in insulin hormone regulation, has exhibited a noteworthy escalation in its prevalence over recent decades. The surge in incidence is notably associated with the proliferation of endocrine-disrupting chemicals (EDCs), which have emerged as primary contributors to the manifestation of insulin resistance and the consequent disruption of beta cell function, ultimately culminating in the onset of diabetes. Consequently, this study endeavors to introduce a model for diabetes that aims to elucidate the ramifications of exposure to EDCs within the diabetic population. In the pursuit of mitigating the deleterious effects of EDC-induced diabetes, we propose a framework for optimal control strategies. The utilization of Pontryagin’s maximum principle serves to explicate the principles governing the optimal control mechanisms within the proposed model. Our findings underscore that heightened concentrations of EDCs play a pivotal role in exacerbating the prevalence of diabetes. To substantiate our model, we employ parameter estimation techniques utilizing a diabetes dataset specific to the demographic context of India. This research contributes valuable insights into the imperative need for proactive measures to regulate and diminish EDC exposure, thereby mitigating the escalating diabetes epidemic.
Keywords
References
- [1] Wu, H., Eggleston, K.N., Zhong, J., Hu, R., Wang, C., Xie, K. et al. How do type 2 diabetes mellitus (T2DM)-related complications and socioeconomic factors impact direct medical costs? A cross-sectional study in rural Southeast China. BMJ Open, 8(11), e020647, (2018).
- [2] World Health Organization, Health Topics, Diabetes. https://www.who.int/healthtopics/diabetes, [Accessed: 15.10.2023].
- [3] The American Diabetes Association®(ADA). https://www.diabetes.org/diabetes, [Accessed: 15.10.2023].
- [4] Scheen, A. Pathophysiology of type 2 diabetes. Acta Clinica Belgica, 58(6), 335-341, (2003).
- [5] International diabetes federation, IDF Diabetes Atlas 2021. https://diabetesatlas.org/, [Accessed: 15.10.2023].
- [6] Institute for Public Health. "National Health Morbidity Survey 2015 (NHMS 2015). Vol. II: Non-Communicable Diseases, Risk Factors & Other Health Problems." Minist. Health Malays. 2: 185-186 (2015). Retrieved from https://www.moh.gov.my/moh/resources/ nhmsreport2015vol2.pdf
- [7] Malaysian Ministry of Health (MMH), 2016. National Strategic Plan for Non-Communicable Disease (NSP- NCD) 2016-2025. Retrieved from https://www.iccp-portal.org/system/ files/plans/MYS_B3_NSP%20NCD%202016-2025%2C%20FINAL.pdf
- [8] Dal Canto, E., Ceriello, A., Rydén, L., Ferrini, M., Hansen, T.B., Schnell, O. et al. Diabetes as a cardiovascular risk factor: An overview of global trends of macro and micro vascular complications. European Journal of Preventive Cardiology, 26(2suppl), 25-32, (2019).
Details
Primary Language
English
Subjects
Biological Mathematics, Dynamical Systems in Applications
Journal Section
Research Article
Publication Date
December 30, 2023
Submission Date
November 29, 2023
Acceptance Date
December 25, 2023
Published in Issue
Year 2023 Volume: 3 Number: 4
APA
Logaprakash, P., & Monica, C. (2023). Optimal control of diabetes model with the impact of endocrine-disrupting chemical: an emerging increased diabetes risk factor. Mathematical Modelling and Numerical Simulation With Applications, 3(4), 318-334. https://doi.org/10.53391/mmnsa.1397575
AMA
1.Logaprakash P, Monica C. Optimal control of diabetes model with the impact of endocrine-disrupting chemical: an emerging increased diabetes risk factor. MMNSA. 2023;3(4):318-334. doi:10.53391/mmnsa.1397575
Chicago
Logaprakash, P., and C. Monica. 2023. “Optimal Control of Diabetes Model With the Impact of Endocrine-Disrupting Chemical: An Emerging Increased Diabetes Risk Factor”. Mathematical Modelling and Numerical Simulation With Applications 3 (4): 318-34. https://doi.org/10.53391/mmnsa.1397575.
EndNote
Logaprakash P, Monica C (December 1, 2023) Optimal control of diabetes model with the impact of endocrine-disrupting chemical: an emerging increased diabetes risk factor. Mathematical Modelling and Numerical Simulation with Applications 3 4 318–334.
IEEE
[1]P. Logaprakash and C. Monica, “Optimal control of diabetes model with the impact of endocrine-disrupting chemical: an emerging increased diabetes risk factor”, MMNSA, vol. 3, no. 4, pp. 318–334, Dec. 2023, doi: 10.53391/mmnsa.1397575.
ISNAD
Logaprakash, P. - Monica, C. “Optimal Control of Diabetes Model With the Impact of Endocrine-Disrupting Chemical: An Emerging Increased Diabetes Risk Factor”. Mathematical Modelling and Numerical Simulation with Applications 3/4 (December 1, 2023): 318-334. https://doi.org/10.53391/mmnsa.1397575.
JAMA
1.Logaprakash P, Monica C. Optimal control of diabetes model with the impact of endocrine-disrupting chemical: an emerging increased diabetes risk factor. MMNSA. 2023;3:318–334.
MLA
Logaprakash, P., and C. Monica. “Optimal Control of Diabetes Model With the Impact of Endocrine-Disrupting Chemical: An Emerging Increased Diabetes Risk Factor”. Mathematical Modelling and Numerical Simulation With Applications, vol. 3, no. 4, Dec. 2023, pp. 318-34, doi:10.53391/mmnsa.1397575.
Vancouver
1.P. Logaprakash, C. Monica. Optimal control of diabetes model with the impact of endocrine-disrupting chemical: an emerging increased diabetes risk factor. MMNSA. 2023 Dec. 1;3(4):318-34. doi:10.53391/mmnsa.1397575
Cited By
An accurate finite difference formula for the numerical solution of delay-dependent fractional optimal control problems
An International Journal of Optimization and Control: Theories & Applications (IJOCTA)
https://doi.org/10.11121/ijocta.1478Modeling different strategies towards control of lung cancer: leveraging early detection and anti-cancer cell measures
Computer Methods in Biomechanics and Biomedical Engineering
https://doi.org/10.1080/10255842.2024.2404540