MATHEMATICAL MODEL FOR DETERMINING DIABETES IN CAPE COAST

Authors

  • Bernard Allotey Jacobs Cape Coast Technical Institute

Keywords:

differential equation, diabetes, glucose, insulin.

Abstract

Diabetes is said to be one of the rising killer diseases globally, claiming one life every eight seconds and a limb lost at every 30 seconds. This has become a burden in the country as the situation has the tendency to weaken the workforce of the nation if much awareness is not induced. The aim of this project is to find out how our body’s metabolism is linked to the disease by modeling the interaction between insulin and glucose. The objective is to use the model to analyse a clinical test for the determining of various forms of diabetes. A nonlinear least square method is used to determine the coefficient parameters of the system based on actual data from Glucose Tolerance test (GTT). The simulations also provide an indicator to diagnose a diabetic condition. Central Regional Teaching Hospital was used as the population and three patients were selected at random for the studies of which one was hyperglycemic (subject B), diabetic (subject C) and the other non-diabetic (subject A). The error between the simulated data and the experimental data was calculated to be very small in subject A and subject C. The case with subject B indicate that our model described above can only be used to diagnose mild diabetes or pre-diabetes, since it was assumed throughout that the deviation of g of G from its optimal value Go is small.

Author Biography

Bernard Allotey Jacobs, Cape Coast Technical Institute

An Instructor with Department of Mathematics, Cape Coast Technical Institute, Ghana

References

Ackerman, N. B., Lien, W. M., Kondi, E. S., and Silverman, N. A. (1969). The blood supply

of experimental liver metastases. I. The distribution of hepatic artery and portal vein blood to" small" and" large" tumors. Surgery, 66(6), 1067.

http://www.ncbi.nlm.nih.gov/pubmed/5402533 Retrieved May 6, 2014

Adubofuor, K. O. M., Ofei, F., Mensah-Adubofour, J., and Owusu, S. K. (1993). Diabetes in

Ghana: a morbidity and mortality analysis. International Diabetes Digest, 4(3), 90-92.

Aikins, A. D. G. (2007). Ghana's neglected chronic disease epidemic: a developmental

challenge. Ghana medical journal, 41(4), 154.

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2350116/ Retrieved May 6, 2014

American Diabetes Association. (2005). Standards of medical care in diabetes. Diabetes care,

, S4-S3 6 http://ci.nii.ac.jp/naid/30026281145/ Retrieved May 6, 2014

Amoah, A. G., Owusu, S. K., and Adjei, S. (2002). Diabetes in Ghana: a community based

prevalence study in Greater Accra. Diabetes research and clinical practice, 56(3), 197-205. http://www.diabetesresearchclinicalpractice.com/article/S0168-8227%2801%2900374-6/abstract Retrieved May 6, 2014

Bagbin, A.K.S.,(2012) Prevalence of diabetes has reached epidemic proportions – WHO

http://www.ghanaweb.com/GhanaHomePage/health/Prevalence-of-diabetes-has-reached-epidemic-proportions-WHO-241852 Retrieved May 6, 2014

Bergman R.N., Ider Y.Z., Bowden C.R., and Cobelli C. (1979) Quantitative estimation of

insulin sensitivity. Am J Physiol. ;236(6):E667–E677.

http://www.ncbi.nlm.nih.gov/pubmed/443421 Retrieved May 6, 2014

Boutayeb, A., Twizell, E. H., Achouayb, K., and Chetouani, A. (2004). A mathematical

model for the burden of diabetes and its complications. Biomedical engineering online, 3(1), 20.

http://biomedical-engineering-online.biomedcentral.com/articles/10.1186/1475-925X-3-20

Cook, S., Auinger, P., Li, C., and Ford, E. S. (2008). Metabolic syndrome rates in united

states adolescents, from the national health and nutrition examination survey, 1999–2002. The Journal of pediatrics, 152(2), 165-170.

Fisher, M. E. (1991). A semiclosed-loop algorithm for the control of blood glucose levels in

diabetics. Biomedical Engineering, IEEE Transactions on, 38(1), 57-61.

http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=68209&url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Farnumber%3D68209 Retrieved May 6, 2014

Furler, S. M., Kraegen, E. W., Smallwood, R. H., and Chisholm, D. J. (1985). Blood glucose

control by intermittent loop closure in the basal mode: computer simulation studies with a diabetic model. Diabetes care, 8(6), 553-561.

http://care.diabetesjournals.org/content/8/6/553.short Retrieved May 6, 2014

Muoio, D. M., and Newgard, C. B. (2008). Molecular and metabolic mechanisms of insulin

resistance and β-cell failure in type 2 diabetes. Nature reviews Molecular cell biology, 9(3), 193-205. http://www.nature.com/nrm/journal/v9/n3/abs/nrm2327.html Retrieved February 20, 2014

Kwach, B., Ongati, O., and Simwa, R. (2011). Mathematical Model for Detecting Diabetes in

the Blood. App Math Sci, 5(6), 279-286. http://s3.amazonaws.com/academia.edu.documents/30898945/kwachAMS5-8-2011.pdf?AWSAccessKeyId=AKIAJ56TQJRTWSMTNPEA&Expires Retrieved March 14, 2014

Lynch, S.M. and Bequette, B.W. (2002). Model predictive control of blood glucose in type I

diabetics using sub- cutaneous glucose measurements. In American Control Conference, Anchorage, Alaska, volume 5, 4039–4043.

Mahaffy, J. M., and Chávez-Ross, A. (2006). Lab Manual for Calculus: A Modeling

Approach for the Life Sciences. http://www-rohan.sdsu.edu/~jmahaffy/courses/f09/math636/hwprobs/labm_3j.pdf Retrieved March 14, 2014

Mahan, L. K. (2004). Krause's food, nutrition, & diet therapy.

http://www.just.edu.jo/CoursesAndLabs/Advanced%20Diet%20Therapy_NF%20769/NF%20769.pdf Retrieved February 20, 2014

Ogden, C. L., Carroll, M. D., & Flegal, K. M. (2008). High body mass index for age among

US children and adolescents, 2003-2006. Jama, 299(20), 2401-2405.

http://jama.jamanetwork.com/article.aspx?articleid=1028638

Rosado, J. L., Caamaño, M. C., Montoya, Y. A., de Lourdes Solano, M., Santos, J. I., and

Long, K. Z. (2009). Interaction of zinc or vitamin A supplementation and specific parasite infections on Mexican infants' growth: a randomized clinical trial. European journal of clinical nutrition, 63(10), 1176-1184.

http://www.nature.com/ejcn/journal/v63/n10/abs/ejcn200953a.html Retrieved March 14, 2014

Shim, J. K., and Siegel, J. G. (2010). Dictionary of accounting terms. Barron's.

Ståhl, F., Johansson, R., and Renard, E. (2010). Post-prandial plasma glucose prediction in

type 1 diabetes based on impulse response models. In Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE (pp. 1324-1327). IEEE.

http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=5626386&url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Farnumber%3D5626386 Retrieved March 14, 2014

Wild, S., Roglic, G., Green, A., Sicree, R., and King, H. (2004). Global prevalence of

diabetes estimates for the year 2000 and projections for 2030. Diabetes care, 27(5), 1047-1053.

http://care.diabetesjournals.org/content/27/5/1047.short Retrieved March 14, 2014

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Published

2016-01-02

How to Cite

Jacobs, B. A. (2016). MATHEMATICAL MODEL FOR DETERMINING DIABETES IN CAPE COAST. AFRICAN JOURNAL OF APPLIED RESEARCH, 2(2). Retrieved from https://www.ajaronline.com/index.php/AJAR/article/view/146