Document Type : Original Article
Authors
1 Department of Medical Informatics, Tarbiat Modarres University, Tehran, Iran
2 Department of Medicine, Kermanshah Univesrsity of Medical Sciences, Iran
Abstract
Despite the increasing number of diabetic patients, self-care plays an important role in the prevention and detection of various complications such as neurological disorders. The aim of this experiment was to investigate the main factors affecting diabetes type 1 and self-care. For this purpose, six volunteer subjects with diabetes type 1 were included. Their glucose levels together with the carbohydrate intake and other factors were recorded four times a day for 30 days. In order to perform statistical analysis, the one-way variance analysis, Pearson correlation coefficient, time series analysis, and the combined time series (panel) analysis were applied. The findings of this study demonstrated that the alteration in blood glucose levels was strongly influenced by carbohydrate intake, physical activity, stress level, amount of sleep, and insulin; while slightly influenced by pills and supplements use, hypoglycemia, insulin sensitivity, alcohol and cigarette use, and comorbidity. In four patients, the self-care score was normal, one patient exhibited high level and the reaming showed low level. For each patient, the error rate was as follows: 6.451, 6.095, 8.819, 7.368, 6.05, 5.856. Regarding to the loss of HbA1c rate after our study, people are advised to control their blood glucose levels based on individual preferences, conditions, lifestyle, and physiology for preventing severe diabetes type 1 conditions and extra cost.
Keywords
2017]. Available from: https://www.idf.org/diabetesatlas/update.
2. Shrivastava SR, Shrivastava PS, Ramasamy J. Role of self-care
in management of diabetes mellitus. J Diabetes Metab Disord.
2013;12(1):14. doi: 10.1186/2251-6581-12-14 pmid:
23497559
3. Jordan DN, Jordan JL. Self-care behaviors of Filipino-
American adults with type 2 diabetes mellitus. J Diabetes
Complications. 2010;24(4):250-8. doi:
10.1016/j.jdiacomp.2009.03.006 pmid: 19615920
4. American Diabetes A. Standards of Medical Care in Diabetes-
2017 Abridged for Primary Care Providers. Clin Diabetes.
2017;35(1):5-26. doi: 10.2337/cd16-0067 pmid: 28144042
5. McManus P, editor Introduction to regression models for
panel data analysis2015: Indiana University Workshop in
Methods.
6. Jachner S, Van den Boogaart G, Petzoldt T. Statistical methods
for the qualitative assessment of dynamic models with time
delay (R Package qualV). J Stat Softw. 2007;22(8):1-30.
7. Georga EI, Protopappas VC, Fotiadis DI. Glucose prediction
in type 1 and type 2 diabetic patients using data driven
techniques. Knowledge-oriented applications in data mining:
IntechOpen; 2011.
8. Aibinu A, Salami M, Shafie A. Blood Glucose Level Prediction
Using Intelligent Based Modeling Techniques. Inst Electrical
Electron Eng. 2010;4(2):1734-7.
9. Jabali AK. Prediction of Patient’s Individual Blood Glucose
Levels from Home Monitored Readings of Type I Diabetics.
Am J Biomed Sci. 2013;5(3):188-96.
10. Majma N, Babamir SM, sensors. Specification and verification
of medical monitoring system using petri-nets. J Med Signals.
2014;4(3):181.
11. Rajasekharan D, Kulkarni V, Unnikrishnan B, Kumar N, Holla
R, Thapar R. Self care activities among patients with diabetes
attending a tertiary care hospital in Mangalore Karnataka,
India. J Ann Med. 2015;5(1):59-64.
12. Parham M, Ryahyn A, Jandaghi M, Daryvandpur A. The effect
of self-care behaviors in diabetic patients. J Qom Univ Med Sci.
2012;6(4):81-7.
13. Galileans F, Zinat Motlagh F, Solhi M. The effect of the
increase in self-care educational program in patients with type
II diabetes. Ilam J Med Sci. 2012;20(1).
14. Nazari E, Nazari S. Selfcare in Type I Diabetes with
Continuous Glucose Monitoring. Iran J Med Inform. 2019;8.
doi: 10.30699/ijmi.v8i1.169.
)