Risk Factors That Lead To Poor Glycemic Control In Type 2 Diabetic Patients Attending Al Diwaniya Diabetes Mellitus Center In 2023

Lara Noori Hamza; Hassan Raji  Jallab

doi:10.61132/obat.v2i5.679

Authors

Lara Noori Hamza Direktorat Kesehatan Al-Diwaniyah
Hassan Raji Jallab Universitas Al-Qadisiyah

DOI:

https://doi.org/10.61132/obat.v2i5.679

Keywords:

Risk Factors, Poor Glycemic Control, Type 2 Diabetes

Abstract

Background: Diabetes mellitus (DM) is the most common metabolic disorder worldwide. DM is the most common chronic illness in adults. It is estimated that 300 million people will have DM by 2025, and it will reach approximately 439 million and the prevalence is estimated to be 7.7% by 2030. The decrease of blood glucose levels in patients with DM decreases the mortality and morbidity rates significantly.Objective: To identify the potential risk factors of poor glycemic control among patients having type2 Diabetes mellitus in Al-diwaniya city. Methods: A total of 340 patients were included in the study. This was cross sectional study conducted in the Diabetes Center at Al-diwaniya city, Iraq, from period of 1^st of February to the 1^st September2023. Based on the cutoff point of Glycosylated hemoglobin of 7, the poor control were the patients with (Glycosylated hemoglobin is ≥ 7) and the good control were the diabetic patient with Glycosylated hemoglobin is <7. A questionnaire developed to gather the demographic, lipid profile, disease characteristics and lifestyles behaviors and filled by the researcher through direct interview. Results: The total number of poor controls was 221 and the good control was 119 patients. There was no significant difference between the two groups regarding sex, age, marital status and occupation. A significant association was observed between the control status and high education level (p=0.001) dyslipidemia (p=0.001), cholesterol level (P=0.002), high TG level (p<0.001), and LDL level (p=0.025). Smoking, Body Mass Index and HDL level were not significant factors (p>0.005). All disease characteristics including the duration, family history of DM, FBS, type of medication were significant factors (p<0.001). Lifestyles behaviors including self-monitoring, healthy diet, physical activity, and adherence were significant factors (p<0.001). Conclusion: The most important potential risk factors for poor control diabetes were dyslipidemia, poor adherence and longer duration of diabetes. Enhancement of education of the patients and their healthcare providers on these factors are great benefit in glycemic control.

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References

Abusaib, M., Fadlyana, E., & Al Ameer, A. (2020). Iraqi Experts Consensus on the Management of Type 2 Diabetes/Prediabetes in Adults. Clinical Medicine Insights: Endocrinology and Diabetes, 13, 1179551420942232. https://doi.org/10.1177/1179551420942232

Al-Moosa, M. R., & Fadlyana, E. (2021). Risk factors associated with poor glycemic control in patients with type two diabetes mellitus in Zakho city. Journal of Contemporary Medicine Sciences, 7(3). https://doi.org/10.22317/jcms.v7i3.970

American Diabetes Association. (2009). Diagnosis and classification of diabetes mellitus. Diabetes Care, 32(Suppl 1), S62–S67. https://doi.org/10.2337/dc09-S062

American Diabetes Association. (2022). Care in diabetes—2022. Diabetes Care, 45, S17. https://doi.org/10.2337/dc22-S001

Cheng, L. J., Wang, W., Lim, S. T., & Wu, V. X. (2019). Factors associated with glycaemic control in patients with diabetes mellitus: A systematic literature review. Journal of Clinical Nursing, 28(9–10), 1433–1450. https://doi.org/10.1111/jocn.14795

Chiefari, E., Arcidiacono, B., Foti, D., & Brunetti, A. (2017). Gestational diabetes mellitus: An updated overview. Journal of Endocrinological Investigation, 40(9), 899–909. https://doi.org/10.1007/s40618-016-0607-5

DeFronzo, R. A. (2004). Pathogenesis of type 2 diabetes mellitus. Medical Clinics of North America, 88(4), 787–835. https://doi.org/10.1016/j.mcna.2004.01.016

ElSayed, N. A., Ali, M. K., & Haffner, S. M. (2023). Classification and diagnosis of diabetes: Standards of care in diabetes-2023. Diabetes Care, 46(Suppl 1), S19–S40. https://doi.org/10.2337/dc23-S002

Forouhi, N. G., & Wareham, N. J. (2019). Epidemiology of diabetes. Medicine (Baltimore), 47(1), 22–27. https://doi.org/10.1016/j.mpmed.2018.10.004

Gribovschi, C. (2013). The methodology of glucose monitoring in type 2 diabetes mellitus. Clujul Medical, 86(2), 93. https://doi.org/10.15386/cjmed-667

Haghighatpanah, M., Nejad, A. S. M., Haghighatpanah, M., Thunga, G., & Mallayasamy, S. (2018). Factors that correlate with poor glycemic control in type 2 diabetes mellitus patients with complications. Osong Public Health and Research Perspectives, 9(4), 167–174. https://doi.org/10.24171/j.phrp.2018.9.4.05

Kayar, Y., Ozen, A., Kizir, S., & Ozturk, F. (2017). Relationship between the poor glycemic control and risk factors, life style and complications. Biomedical Research, 28(4), 1581–1586.

Mamo, Y., Bekele, F., Nigussie, T., & Zewudie, A. (2019). Determinants of poor glycemic control among adult patients with type 2 diabetes mellitus in Jimma University Medical Center, Jimma zone, south west Ethiopia: A case control study. BMC Endocrine Disorders, 19(1), 91. https://doi.org/10.1186/s12902-019-0421-0

Mansour, A. A., Abbas, H., & Al-Khader, A. (2020). Prevalence and correlation of glycemic control achievement in patients with type 2 diabetes in Iraq: A retrospective analysis of a tertiary care database over a 10-year period. International Journal of Clinical Medicine, 11, 77–84. https://doi.org/10.4236/ijcm.2020.113008

Mansour, Z., Hadi, R., & El Hajj, H. (2020). Non-communicable diseases in Lebanon: Results from World Health Organization STEPS survey 2017. Public Health, 187, 120–126. https://doi.org/10.1016/j.puhe.2020.07.010

Moon, S. J., Lee, W.-Y., Hwang, J. S., Hong, Y. P., & Morisky, D. E. (2017). Accuracy of a screening tool for medication adherence: A systematic review and meta-analysis of the Morisky Medication Adherence Scale-8. PLoS One, 12(11), e0187139. https://doi.org/10.1371/journal.pone.0187139

Nathan, D. M., & Delahanty, L. (2005). Beating Diabetes. McGraw Hill Professional.

Omer, W., & Al Hadithi, T. (2017). Developing a socioeconomic index for health research in Iraq. Eastern Mediterranean Health Journal, 23(10), 670–677. https://doi.org/10.26719/2017.23.10.670

Ong, S. E., Sulaiman, N., Noor, N. M., & Ng, S. H. (2018). Assessing the influence of health systems on Type 2 Diabetes Mellitus awareness, treatment, adherence, and control: A systematic review. PLoS One, 13(3), e0195086. https://doi.org/10.1371/journal.pone.0195086

Oza-Frank, R., Ali, M. K., Vaccarino, V., & Narayan, K. M. V. (2009). Asian Americans: Diabetes prevalence across U.S. and World Health Organization weight classifications. Diabetes Care, 32(9), 1644–1646. https://doi.org/10.2337/dc09-0573

Pinchevsky, Y., Butkow, N., Raal, F. J., Chirwa, T., & Rothberg, A. (2020). Demographic and clinical factors associated with development of Type 2 Diabetes: A review of the literature. International Journal of General Medicine, 13, 121–129. https://doi.org/10.2147/IJGM.S226010

Radin, M. S. (2014). Pitfalls in hemoglobin A1c measurement: When results may be misleading. Journal of General Internal Medicine, 29(2), 388–394. https://doi.org/10.1007/s11606-013-2595-x

Shepard, J. G., Airee, A., Dake, A. W., McFarland, M. S., & Vora, A. (2015). Limitations of A1c interpretation. Southern Medical Journal, 108(12), 724–729. https://doi.org/10.14423/smj.0000000000000381

Uttra, K. M., Nair, K., & Rao, S. (2011). Lipid profile of patients with diabetes mellitus (A multidisciplinary study). World Applied Sciences Journal, 12(9), 1382–1384.

Vana, D. R., Adapa, S., Prasad, V. S. S., Choudhury, A., & Ahuja, G. (2019). Diabetes mellitus types: Key genetic determinants and risk assessment. Genetics and Molecular Research, 18(2), 27. https://doi.org/10.4238/gmr18227

Xu, G., Liu, B., & Zhang, C. (2018). Prevalence of diagnosed type 1 and type 2 diabetes among US adults in 2016 and 2017: Population based study. BMJ, 362, k1497. https://doi.org/10.1136/bmj.k1497

Zhang, X., & Zhang, X. (2010). A1C level and future risk of diabetes: A systematic review. Diabetes Care, 33(7), 1665–1673. https://doi.org/10.2337/dc09-1939

Zhou, B., Lu, Y., Hu, Y., Zhang, Y., & Qi, L. (2016). Worldwide trends in diabetes since 1980: A pooled analysis of 751 population-based studies with 4.4 million participants. The Lancet, 387(10027), 1513–1530. https://doi.org/10.1016/S0140-6736(16)00618-8