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DOI: 10.1055/s-0045-1810619
Factors of Poor Glycemic Control among Individuals with Diabetes in Atbara, Sudan
Funding and Sponsorship None.
Abstract
Background
Understanding of factors influencing diabetes control is crucial for effective interventions to improve glycemic control.
Objective
We aimed to determine poor glycemic control in patients with type 2 diabetes (T2D) in Atbara Diabetes Centers, Sudan,
Patients and Methods
An observational, cross-sectional, multicenter-based study was conducted from June to December 2023. The study included Sudanese patients with T2D attending care centers. The sample size was 385 participants by convenience sampling. Data were collected through face-to-face interviews by a structured questionnaire.
Results
The majority of the participants were between 40 and 60 years old (47.3%), female (56.4%), married (74.3%), and living in urban areas (74.8%). Patient-related factors, such as obesity (20.8%) and sedentary lifestyles (15.1%), revealed that many participants had habits and lifestyles that negatively impacted health. However, most participants had good medication adherence and awareness of diabetes control (68.6 and 53%, respectively). Many participants reported experiencing a stressful lifestyle (52.5%). Only 51.9% had well-controlled diabetes. Age, medication adherence, and diabetes awareness were significantly associated with glycemic control. Predictors of poor glycemic control included age above 60 years, poor medication adherence, poor awareness of diabetes, and not undergoing regular monitoring.
Conclusion
Poor glycemic control is associated with inadequate self-management practices, a lack of proper education and awareness about diabetes management, limited access to healthcare services, and comorbidities. These findings should inform healthcare providers and policymakers about implementing targeted interventions to address the specific needs of individuals with T2D. By addressing these factors and implementing effective interventions, it is possible to enhance glycemic control and ultimately improve the overall health outcomes of this population.
Introduction
Type 2 diabetes (T2D) accounts for ∼90% of all cases of diabetes.[1] In T2D, the insulin response is diminished, which is defined as insulin resistance.[2] There is growing evidence that insulin is ineffective and is initially countered by an increase in insulin production to maintain glucose homeostasis, but over time, insulin production decreases, resulting in T2D. T2D is most common in people older than 45 years.[3] Diabetes is a major public health problem locally, regionally, and internationally. According to the International Diabetes Federation (IDF), ∼415 million adults between 20 and 79 years old have DM.[1] T2D is a global public health burden, which is expected to increase to another 200 million by 2040.[1] [2] In Sudan, one publication has shown that the prevalence of T2D among adults has increased to 19%.[4]
Patients with an HbA1c greater than 6.5% (48 mmol/mol) are diagnosed with DM. HbA1c is a convenient, rapid, standardized test that shows less variation due to the use of preanalytical variables. It is not strongly affected by acute illness or stress.[5]
Studies have shown that many factors interact to control blood sugar, including factors related to the patient, the doctor, and the health system.
Concerning patients, self-management behavior appears to influence glycemic control, and diabetic patients should be consistently advised to restrict sugar intake, exercise, stop smoking, and adhere to medication instructions. In addition to health insurance, the affordability of health care services, the availability of health professionals, and good insulin storage influence glycemic control.[5] [6]
Several factors can contribute to poor glycemic control, including a lack of access to healthcare, inadequate diabetes education, noncompliance with treatment plans, medication side effects, psychological factors, socioeconomic conditions, and cultural beliefs. Addressing these factors is crucial in optimizing diabetes management.[7] Intensive medical treatment combined with diabetes self-management education has been demonstrated to significantly reduce the risk of diabetes-related complications by 50 to 75%. Furthermore, this approach is associated with cost savings of approximately $79,280 per individual and can extend life expectancy by an average of 6 years.[8] In Saudi Arabia, Alshahri et al assessed self-management care and HbA1c levels among T2D patients and the factors that may be associated with poor control. HbA1c data were extracted from patients' records. Most of the participants (65%) were found to have poor glycemic control. Glucose management was better in patients with T2D for more than 5 years.[9]
A Sudanese study by Omar and his colleagues showed that the prevalence rates of T2D, newly diagnosed T2DM, and uncontrolled T2D were 20.8, 10.0, and 80.0%, respectively. Logistic regression analysis showed no significant association between education, marital status, body mass index, waist circumference, and diabetes control. However, older age and a family history of DM were associated with T2D. They concluded that the prevalence of T2D is high among the Sudanese population, especially in older people and those with a family history of DM. The high prevalence of uncontrolled DM in this setting is another hidden burden.[10]
Although many international studies have examined factors contributing to poor glycemic control, limited research has been conducted in Northern Sudan, where unique cultural, dietary, and healthcare access factors may influence diabetes management. Understanding these local dynamics is essential for designing effective, context-specific interventions.
Thus, this study aims to identify the factors contributing to poor glycemic control, informing the necessary interventions to improve glycemic control and prevent related complications.
Patients and Methods
Study Design and Setting
This study was an observational, cross-sectional, multicenter-based study. The study was conducted in selected diabetes care centers in Atbara, River Nile State, Sudan. In general, these diabetes care centers provide comprehensive care and support for individuals with diabetes. These centers are dedicated to promoting proper management of diabetes through various functions. They offer regular medical check-ups and consultations to monitor blood sugar levels and provide necessary medications. They also provide education and guidance on healthy eating habits, exercise routines, and self-care practices to manage the condition effectively.
Additionally, they offer specialized services such as diabetic foot care, eye examinations, and counseling to prevent diabetes-related complications. Ultimately, they aim to increase the quality of life of individuals with diabetes by providing holistic care and empowering them with the knowledge and tools to live well with their condition. The study was conducted from June to December 2023.
Study Population
Adult patients with T2D who were attending diabetes care centers in Atbara within the study period and agreed to participate in the study were included. The sample size of the study was determined through the following formula: n = ( Z 2 × ( P × q))/ e 2, where n is the sample size required by the study, Z is the determined area under the normal curve by the desired confidence interval (CI: 95%), and P is the proportion of the main attribute of the study (the expected proportion of diabetes poor control [based on HbA1c] is unknown in the state, p = 0.5, p = 1–p = 1–0.5 = 0. 5 and e = the desired precision (e = 0.05). n = 385 study participants. Convenience sampling was used.
Data Collection and Analysis
Data were collected via direct face-to-face interviews with the participants using a comprehensive, structured, closed-ended questionnaire covering sociodemographic characteristics, clinical characteristics, patients, and service-related factors that affect glycemic control and diabetes control data.
The data were entered, and analyzed via SPSS version 28.0. Descriptive statistics regarding frequency tables, graphs, and means and standard deviations were used. Bivariable analysis was performed to determine the associations between the risk factors for diabetes control via the chi-square test, and a p-value of 0.05 or less was considered statistically significant. A logistic regression test was performed to determine the predictors of glycemic control.
Results
Sociodemographic Characteristics of the Participants
Among the participants, 47.3% were aged between 40 and 60, and 42.1% were above 60 years. A total of 56.4% were females, 74.3% were married, and 74.8% were from urban areas. The socioeconomic class varied: 19.5% were classified as low, 71.4% as middle, and 9.1% as high. 15.3% were illiterate, 34.8% had a primary education, and 26.2% had a bachelor's degree. 42.3% were homemakers. Among the participants, 39.5% had no other chronic diseases, and 35.3% had hypertension ([Table 1]).
Patient-Related Factors that Affect Diabetes Control
A total of 20.8% of the participants were obese, 13.5% were smokers, 1.3% consumed alcohol, 15.1% had a sedentary lifestyle, and 30.4% had a high intake of unhealthy food. More than two-thirds of the participants (68.6%) had good medication adherence. Concerning awareness of diabetes control, 53.0% had good awareness. It is worth noting that medication adherence and diabetes awareness were evaluated using a structured questionnaire that categorized participants' responses into “good,” “average,” or “poor.” These classifications were based on participants' subjective self-assessments rather than objective or validated scoring criteria. While practical in the study context, this approach may limit precision and replicability across different settings. The most common form of diabetes treatment was oral hypoglycemic agents (55.6%), followed by insulin (45.2%) and diet control (11.9%). Moreover, 52.5% reported experiencing a stressful lifestyle ([Table 2]).
Service-Related Factors that Can Affect Diabetes Control
During the visit, 91.9% of the participants reported receiving counseling on diabetes care, and nearly two-thirds reported that the physicians did regular monitoring and testing for them. A total of 72.5% of them reported that they had accessible treatment and health services ([Table 2]).
Glycemic Control
The mean (± SD) HbA1c level was 8.8% (± 2.5). The minimum HbA1c level was 3.5%, whereas the maximum was 15%. In terms of glycemic control, only 51.9% of the participants had well-controlled diabetes, while the remaining 48.1% had uncontrolled diabetes.
Cross-tabulation and chi-square tests were performed to determine the associations between demographic and patient-related factors and glycemic control among the participants. The analysis revealed that glycemic control was significantly associated with age, medication adherence, relevant awareness of diabetes and the control, receiving counseling on diabetes, and receiving regular monitoring and testing (p = 0.037, < 0.001, < 0.001, 0.008, < 0.001, respectively; [Table 3]).
Multivariate Analysis
Logistic regression analysis was conducted to determine the main predictors of poor glycemic control among the participants. The predictors included age, relevant awareness of diabetes, and regular monitoring and testing. Participants older than 60 years had greater odds of having poor glycemic control than those younger than 40 years (OR = 2.79, p = 0.014). Participants with average (OR = 4.00, p = 0.000) and poor (OR = 15.78, p = 0.001) diabetes awareness had higher odds of poor glycemic control than those with good awareness. Not undergoing regular monitoring and testing was significantly associated with increased odds of poor glycemic control (OR = 2.66, p = 0.000). Other demographic, patient, and service-related factors were not significantly related to glycemic control ([Table 4]).
Discussion
Diabetes has become a global epidemic, affecting millions of individuals worldwide. In Sudan, the prevalence of diabetes has been steadily increasing, posing significant challenges to the healthcare system. Glycemic control is a cornerstone in managing diabetes, as it directly impacts the overall health outcomes and quality of life of individuals with this condition. Despite advancements in treatment options and medical interventions, a considerable proportion of individuals with diabetes still struggle to achieve optimal glycemic control. By understanding the factors influencing poor glycemic control, healthcare professionals and policymakers can gain insights into developing tailored interventions and strategies to improve outcomes and lower the burden of complications associated with diabetes. The findings from this assessment will contribute to the body of knowledge surrounding diabetes management in Sudan and provide a basis for further research and intervention development.
The mean HbA1c level was 8.8%, with a standard deviation of 2.5%. Moreover, only 51.9% of the participants demonstrated well-controlled diabetes, while the remaining 48.1% had uncontrolled diabetes. This finding aligns with earlier research that has reported suboptimal glycemic control in individuals with diabetes. For example, Babaniamansour et al[11] reported an average HbA1c of 8.5% among diabetic patients, indicating similar patterns of poor control. However, their study was conducted in a different healthcare context, and variations in healthcare delivery, access to medications, and patient education programs may influence such outcomes. While our findings are comparable, the systemic and cultural differences between settings should be considered when interpreting these similarities.
In our study, HbA1c levels ranged from a minimum of 3.5 to a maximum of 15, reflecting significant variability in glycemic control. This broad range suggests that a considerable proportion of individuals are living with poorly managed diabetes. Adham et al[12] reported a similar distribution in their cohort. Although their results parallel ours, their study was based on a different regional and clinical setting, which may have distinct approaches to diabetes screening, patient follow-up, and management guidelines. Therefore, such similarities in HbA1c distribution may not necessarily reflect identical underlying causes or patient behaviors.
Further analysis showed that 51.9% of participants had well-controlled diabetes, while 48.1% had poor glycemic control. This pattern is consistent with findings from studies by McBrien et al[13] and Yan et al,[14] which also reported that less than half of the individuals with diabetes achieved recommended glycemic targets. Though consistent in outcome, these studies were conducted across varying health systems and cultural environments, where factors such as the cost of diabetes care, insurance coverage, and societal norms related to health may significantly influence glycemic outcomes. Thus, while these findings suggest a widespread challenge, the degree to which these patterns are generalizable remains uncertain and should be considered in light of contextual differences.
A significant association was observed between age and glycemic control (p = 0.037), where participants older than 60 years had a greater proportion of poor glycemic control than those younger than 40 years. This finding is supported by previous studies, such as that of Sinclair et al,[15] who reported higher HbA1c levels among older adults with diabetes. Munshi et al[16] also noted that older individuals demonstrated greater glycemic variability and increased rates of both hypo- and hyperglycemia. These findings are biologically plausible, as aging is associated with decreased β-cell function, insulin resistance, comorbidities, and functional limitations. However, it is important to recognize that aging populations in different countries may not experience these challenges similarly. In some health systems, older adults have better access to structured care, while in others, limited support and complex medication regimens may compound the problem. Thus, while the association between age and poor glycemic control appears consistent across studies, the underlying contributing factors may vary by context.
An interesting observation was the relationship between sex and glycemic control. Although not statistically significant (p = 0.056), more females had well-controlled glycemic levels than males. Several studies support this trend. For example, Jones et al[17] and Almobarak et al[18] found no significant difference in glycemic control between sexes, which aligns with our findings. However, contrary to ours, Johnson et al[19] reported better glycemic control among males. These inconsistencies may be due to variations in study populations, sampling methods, and sociocultural factors influencing health behavior. For instance, sex roles and expectations, psychological stress, and access to healthcare services can differ markedly across societies. Additionally, hormonal influences, such as the effects of estrogen on insulin sensitivity, as noted by Mauvais-Jarvis et al,[20] may also contribute to differences. However, these effects could be modulated by genetic, nutritional, and environmental factors that vary between countries.
The lack of a significant relationship between health insurance and glycemic control (p = 0.286) is consistent with the findings of Bakris et al,[21] who also observed no clear difference between insured and uninsured individuals. While health insurance is typically assumed to enhance access to healthcare services, its impact on glycemic control is not always straightforward. Access alone may not ensure proper disease management; treatment adherence, availability of medications, patient literacy, and quality of care also play critical roles. In lower-resource settings, even insured patients may face barriers such as limited drug availability or overburdened clinics, which can compromise glycemic outcomes.
Logistic regression analysis identified several key predictors of poor glycemic control. Participants older than 60 years had significantly higher odds of poor control than those younger than 40 years, reinforcing the age-related challenges previously discussed and supporting findings from Huo et al,[22] who similarly identified age as a determinant of glycemic control. Medication adherence also emerged as a strong predictor; individuals with average or poor adherence had markedly higher odds of poor glycemic control than those with good adherence. Additionally, lower levels of diabetes awareness were associated with poorer glycemic outcomes. Interestingly, while lack of counseling was not a significant factor, infrequent monitoring and testing were significantly associated with worse control, again in line with the findings by Huo et al.[22] These results emphasize that, beyond demographic factors, behavioral and system-level variables play a crucial role in glycemic management. However, the strength and nature of these associations may differ depending on local healthcare infrastructure, patient support systems, and cultural attitudes toward chronic disease, suggesting a need for context-specific strategies in diabetes care. Notably, some odd ratios reported wide confidence intervals, indicating statistical imprecision. This may be attributed to the relatively small sample size or low event frequency, and these estimates should be interpreted cautiously.
Our study also found a strong association between medication adherence and glycemic control (p < 0.001). Participants with good adherence were significantly more likely to have well-controlled diabetes. These results align with previous research, including a study published in the Journal of Diabetes Research [23] and another by McKnight et al,[24] highlighting the importance of medication adherence in achieving glycemic targets. While adherence is a universal factor in diabetes control, cultural attitudes toward medication, understanding of treatment plans, and trust in healthcare providers can differ across regions. These factors should be considered when comparing findings across diverse populations.
Awareness of diabetes also emerged as a key predictor of glycemic control. Participants with average or poor awareness had higher odds of poor control than those with good awareness. This echoes the findings by McKnight et al,[24] who linked a lack of self-monitoring and awareness to suboptimal glycemic outcomes. Again, while the association holds across studies, awareness is shaped by local education systems, public health campaigns, and cultural perceptions of chronic disease, which vary by context and may influence the degree to which these findings are applicable elsewhere.
The findings of our study must be seen in the light of some limitations. First, it was a cross-sectional study that targeted individuals who attended diabetes centers in Atbara. Consequently, the sample may not be fully representative of all diabetic patients within the broader population, as those who seek care at these centers may have different characteristics and management experiences compared with those who do not. Moreover, convenience sampling further limits the generalizability of our findings, as it may introduce selection bias and reduce the sample's representativeness.
Furthermore, using interview-based questionnaires introduces the potential for recall bias, as participants may not accurately remember or report their behaviors and health information. Similarly, medication adherence was self-reported and not validated through objective methods such as pharmacy refill records, which may affect the reliability of adherence data.
Additionally, our analysis did not include various modalities of therapies that could influence glycemic control. The exclusion of certain treatment options limits the comprehensiveness of our findings and may overlook important variables that contribute to diabetes management in this population.
Conclusion
This study provides valuable insights into the factors influencing glycemic control among individuals with diabetes. These findings underscore the importance of patient education and regular monitoring in managing diabetes effectively. Future research should focus on developing interventions targeting these areas to improve glycemic control among individuals with diabetes.
Conflict of Interest
None declared.
Authors' Contributions
E.O.E.S. was involved in the conception of the research, study design, acquisition of data, and drafting the manuscript. S.K.M.N. has contributed to the research design and the critical revision of the work. S.B. analyzed the data and reviewed the final draft. S.M. and H.S.A.M.M. were involved in drafting the manuscript and in critical revision of the final draft. All authors have approved the final version to be published. All authors agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy and integrity of any part of the work are properly investigated and resolved.
All the authors approved the final version of the manuscript.
Ethical Considerations
The IRB of the Faculty of Medicine, Nile Valley University, granted ethical clearance and approval for this research. All participants provided informed consent.
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References
- 1 Zheng Y, Ley SH, Hu FB. Global aetiology and epidemiology of type 2 diabetes mellitus and its complications. Nat Rev Endocrinol 2018; 14 (02) 88-98
- 2 Martinez LC, Sherling D, Holley A. The screening and prevention of diabetes mellitus. Prim Care 2019; 46 (01) 41-52
- 3 Chinese Diabetes Society, National Office for Primary Diabetes Care. National guidelines for the prevention and control of diabetes in primary care(2018). [article in Chinese]. Zhonghua Nei Ke Za Zhi 2018; 57 (12) 885-893
- 4 Noor SK, Elmadhoun WM, Bushara SO. et al. Glycemic control in Sudanese individuals with type 2 diabetes: population based study. Diabetes Metab Syndr 2016;
- 5 Ahmad NS, Islahudin F, Paraidathathu T. Factors associated with good glycemic control among patients with type 2 diabetes mellitus. J Diabetes Investig 2014; 5 (05) 563-569
- 6 Pringle M, Stewart-Evans C, Coupland C, Williams I, Allison S, Sterland J. Influences on control in diabetes mellitus: patient, doctor, practice, or delivery of care?. BMJ 1993; 306 (6878) 630-634
- 7 Elbagir MN, Eltom MA, Elmahadi EM, Kadam IM, Berne C. A population-based study of the prevalence of diabetes and impaired glucose tolerance in adults in northern Sudan. Diabetes Care 1996; 19 (10) 1126-1128
- 8 Nathan DM, Genuth S, Lachin J. et al; Diabetes Control and Complications Trial Research Group. The effect of intensive treatment of diabetes on the development and progression of long-term complications in insulin-dependent diabetes mellitus. N Engl J Med 1993; 329 (14) 977-986
- 9 Alshahri BK, Bamashmoos M, Alnaimi MI. et al. Assessment of self-management care and glycated hemoglobin levels among type 2 diabetes mellitus patients: a cross-sectional study from the Kingdom of Saudi Arabia. Cureus 2020; 12 (12) e11925
- 10 Omar SM, Musa IR, ElSouli A, Adam I. Prevalence, risk factors, and glycaemic control of type 2 diabetes mellitus in eastern Sudan: a community-based study. Ther Adv Endocrinol Metab 2019; 10: 2042018819860071
- 11 Babaniamansour S, Aliniagerdroudbari E, Niroomand M. Glycemic control and associated factors among Iranian population with type 2 diabetes mellitus: a cross-sectional study. J Diabetes Metab Disord 2020; 19 (02) 933-940
- 12 Adham M, Froelicher ES, Batieha A, Ajlouni K. Glycaemic control and its associated factors in type 2 diabetic patients in Amman, Jordan. East Mediterr Health J 2010; 16 (07) 732-9 PMID: 20799529
- 13 McBrien KA, Manns BJ, Hemmelgarn BR. et al. The association between sociodemographic and clinical characteristics and poor glycaemic control: a longitudinal cohort study. Diabet Med 2016; 33 (11) 1499-1507
- 14 Yan Y, Wu T, Zhang M, Li C, Liu Q, Li F. Prevalence, awareness and control of type 2 diabetes mellitus and risk factors in Chinese elderly population. BMC Public Health 2022; 22 (01) 1382
- 15 Sinclair AJ, Abdelhafiz AH, Rodriguez-Mañas L. Frailty and sarcopenia – newly emerging and high impact complications of diabetes. J Diabetes Complications 2019; 33 (12) 107417
- 16 Munshi MN, Pandya N, Umpierrez GE. et al. Diabetic hypoglycemia: a review of the risk factors, consequences and prevention. Diabetes Care 2018; 36 (11) 3542-3549
- 17 Jones GC, Hitman GA, Edwardson JA. Gender and glycemic control in type 2 diabetes: Is there a link?. J Diabetes Complications 2015; 29 (08) 1137-1144
- 18 Almobarak AO, Noor SK, Elmadhoun WM. et al. Metabolic control targets in Sudanese adults with type 1 diabetes: a population-based study. J Family Med Prim Care 2017; 6 (02) 374-379
- 19 Johnson DA, Bentley TG, Vickers KS. et al. Differences in glycemic control outcomes for female and male adults with type 1 diabetes: results from the T1D Exchange Clinic Registry. BMJ Open Diabetes Res Care 2019; 7 (01) e000714
- 20 Mauvais-Jarvis F, Arnold AP, Reue K. A guide for the design of preclinical studies on sex differences in metabolism. Cell Metab 2013; 18 (06) 705-716
- 21 George Bakris M, Blonde MDLL, Andrew JM. et al. Standards of medical care in diabetes - 2015. Diab Care J Clin Appl Res Educ 2015; 38: S1-S99
- 22 Huo L, Deng W, Shaw JE. et al. Factors associated with glycemic control in type 1 diabetes patients in China: a cross-sectional study. J Diabetes Investig 2020; 11 (06) 1575-1582
- 23 Krapek K, King K, Warren SS. et al. Medication adherence and associated hemoglobin A1c in type 2 diabetes. Ann Pharmacother 2004; 38 (09) 1357-1362
- 24 McKnight JA, Wild SH, Lamb MJ. et al. Glycaemic control of Type 1 diabetes in clinical practice early in the 21st century: an international comparison. Diabet Med 2015; 32 (08) 1036-1050
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References
- 1 Zheng Y, Ley SH, Hu FB. Global aetiology and epidemiology of type 2 diabetes mellitus and its complications. Nat Rev Endocrinol 2018; 14 (02) 88-98
- 2 Martinez LC, Sherling D, Holley A. The screening and prevention of diabetes mellitus. Prim Care 2019; 46 (01) 41-52
- 3 Chinese Diabetes Society, National Office for Primary Diabetes Care. National guidelines for the prevention and control of diabetes in primary care(2018). [article in Chinese]. Zhonghua Nei Ke Za Zhi 2018; 57 (12) 885-893
- 4 Noor SK, Elmadhoun WM, Bushara SO. et al. Glycemic control in Sudanese individuals with type 2 diabetes: population based study. Diabetes Metab Syndr 2016;
- 5 Ahmad NS, Islahudin F, Paraidathathu T. Factors associated with good glycemic control among patients with type 2 diabetes mellitus. J Diabetes Investig 2014; 5 (05) 563-569
- 6 Pringle M, Stewart-Evans C, Coupland C, Williams I, Allison S, Sterland J. Influences on control in diabetes mellitus: patient, doctor, practice, or delivery of care?. BMJ 1993; 306 (6878) 630-634
- 7 Elbagir MN, Eltom MA, Elmahadi EM, Kadam IM, Berne C. A population-based study of the prevalence of diabetes and impaired glucose tolerance in adults in northern Sudan. Diabetes Care 1996; 19 (10) 1126-1128
- 8 Nathan DM, Genuth S, Lachin J. et al; Diabetes Control and Complications Trial Research Group. The effect of intensive treatment of diabetes on the development and progression of long-term complications in insulin-dependent diabetes mellitus. N Engl J Med 1993; 329 (14) 977-986
- 9 Alshahri BK, Bamashmoos M, Alnaimi MI. et al. Assessment of self-management care and glycated hemoglobin levels among type 2 diabetes mellitus patients: a cross-sectional study from the Kingdom of Saudi Arabia. Cureus 2020; 12 (12) e11925
- 10 Omar SM, Musa IR, ElSouli A, Adam I. Prevalence, risk factors, and glycaemic control of type 2 diabetes mellitus in eastern Sudan: a community-based study. Ther Adv Endocrinol Metab 2019; 10: 2042018819860071
- 11 Babaniamansour S, Aliniagerdroudbari E, Niroomand M. Glycemic control and associated factors among Iranian population with type 2 diabetes mellitus: a cross-sectional study. J Diabetes Metab Disord 2020; 19 (02) 933-940
- 12 Adham M, Froelicher ES, Batieha A, Ajlouni K. Glycaemic control and its associated factors in type 2 diabetic patients in Amman, Jordan. East Mediterr Health J 2010; 16 (07) 732-9 PMID: 20799529
- 13 McBrien KA, Manns BJ, Hemmelgarn BR. et al. The association between sociodemographic and clinical characteristics and poor glycaemic control: a longitudinal cohort study. Diabet Med 2016; 33 (11) 1499-1507
- 14 Yan Y, Wu T, Zhang M, Li C, Liu Q, Li F. Prevalence, awareness and control of type 2 diabetes mellitus and risk factors in Chinese elderly population. BMC Public Health 2022; 22 (01) 1382
- 15 Sinclair AJ, Abdelhafiz AH, Rodriguez-Mañas L. Frailty and sarcopenia – newly emerging and high impact complications of diabetes. J Diabetes Complications 2019; 33 (12) 107417
- 16 Munshi MN, Pandya N, Umpierrez GE. et al. Diabetic hypoglycemia: a review of the risk factors, consequences and prevention. Diabetes Care 2018; 36 (11) 3542-3549
- 17 Jones GC, Hitman GA, Edwardson JA. Gender and glycemic control in type 2 diabetes: Is there a link?. J Diabetes Complications 2015; 29 (08) 1137-1144
- 18 Almobarak AO, Noor SK, Elmadhoun WM. et al. Metabolic control targets in Sudanese adults with type 1 diabetes: a population-based study. J Family Med Prim Care 2017; 6 (02) 374-379
- 19 Johnson DA, Bentley TG, Vickers KS. et al. Differences in glycemic control outcomes for female and male adults with type 1 diabetes: results from the T1D Exchange Clinic Registry. BMJ Open Diabetes Res Care 2019; 7 (01) e000714
- 20 Mauvais-Jarvis F, Arnold AP, Reue K. A guide for the design of preclinical studies on sex differences in metabolism. Cell Metab 2013; 18 (06) 705-716
- 21 George Bakris M, Blonde MDLL, Andrew JM. et al. Standards of medical care in diabetes - 2015. Diab Care J Clin Appl Res Educ 2015; 38: S1-S99
- 22 Huo L, Deng W, Shaw JE. et al. Factors associated with glycemic control in type 1 diabetes patients in China: a cross-sectional study. J Diabetes Investig 2020; 11 (06) 1575-1582
- 23 Krapek K, King K, Warren SS. et al. Medication adherence and associated hemoglobin A1c in type 2 diabetes. Ann Pharmacother 2004; 38 (09) 1357-1362
- 24 McKnight JA, Wild SH, Lamb MJ. et al. Glycaemic control of Type 1 diabetes in clinical practice early in the 21st century: an international comparison. Diabet Med 2015; 32 (08) 1036-1050