Predictors of poor glycemic control among patients with type 2 diabetes on follow-up care at a tertiary healthcare setting in Ethiopia

Oxidative Stress and Asprosin Levels in Type 2 Diabetic Patients with Good and Poor Glycemic Control

Objectives: HbA1c is the most widely used test as an indicator of glucoregulation in patients with type 2 diabetes mellitus (T2DM). Asprosin and oxidative stress levels can be reduced with good glycemic control (GC) and thus prevented or delayed micro/macro complications in patients with T2DM. The relationship between asprosin, which is thought to affect GC, and oxidative stress parameters such as lipid hydroperoxides (LOOHs), glutathione (GSH), malondialdehyde (MDA), superoxide dismutase (Cu,Zn-SOD), and total antioxidant capacity (TAC) was evaluated in T2DM patients. Materials and Methods: The study was conducted prospectively in 75 healthy people admitted to the hospital for a general health check-up and 150 T2DM patients treated in the diabetes outpatient clinic. The patient's glycemic status measurements were categorized as good glycemic control group (GGC) is defined as HbA1c < 7 and poor glycemic control (PGC) group is defined as HbA1c ≥ 7. Results: The study found a consistent increase in LOOH and MDA levels across the control, GGC, and PGC groups, while GSH, Cu/Zn-SOD, and TAC levels decreased in these respective groups. Additionally, asprosin levels showed a gradual rise in all groups. Positive correlations were observed between asprosin levels and various metabolic and oxidative stress markers, including BMI, WC, FBG, insulin, homeostasis model assessment for insulin resistance (HOMA-IR), DM duration, LOOH, and MDA, while negative correlations were noted with GSH, Cu/Zn-SOD, and TAC specifically in the PGC group. Furthermore, multivariate regression analysis identified HOMA-IR as the primary influencing factor on asprosin levels in PGC patients. Conclusions: Current glycemic dysregulation may lead to increased circulating asprosin and oxidative stress, which cause complications. Since asprosin levels may be an important hormonal factor in determining GC in T2DM, the use of this hormone may be recommended in the future to accelerate therapeutic approaches in T2DM. Early diagnosis and appropriate treatment may delay the development and progression of diabetic complications.

Time to first optimal glycemic control and its predictors among adult type 2 diabetes patients in Amhara Regional State comprehensive specialized hospitals, Northwest Ethiopia

BACKGROUND

Inadequate glycemic management in type 2 diabetes Mellitus patients is a serious public health issue and a key risk factor for progression as well as diabetes-related complications. The main therapeutic goal of preventing organ damage and other problems caused by diabetes is glycemic control. Knowing when to modify glycemic control in type 2 diabetes Mellitus is crucial for avoiding complications and early drug intensifications.

METHODS

An institutional based retrospective follow-up study was undertaken among 514 eligible adult diabetes patients in Amhara region Comprehensive Specialized Hospitals, Northwest Ethiopia, from January 2017 to January 2022. Simple random sampling technique was used to select study participants. The Kaplan Meier curve was used to assess the survival status of categorical variables, and the log-rank test was used to compare them. The cox proportional hazard model was fitted to identify the predictors of time to first optimal glycemic control. Variables with a p-value < 0.05 were considered to be statistically significance at 95% confidence interval.

RESULTS

A total of 514 patient records (227 males and 287 females) were reviewed in this study. The median time to first optimal glycemic control among the study population was 8.4 months IQR (7.6-9.7). The predictors that affect the time to first optimal glycemic control were age group ((AHR = 0.63, 95% CI = 0.463, 0.859 for 50-59 years), (AHR = 0.638, 95% CI = 0.471, 0.865 for 60-69 years), and (AHR = 0.480, 95% CI = 0.298, 0.774 for > = 70 years)), diabetes neuropathy (AHR = 0.629, 95% CI = 0.441,0.900), hypertension (AHR = 0.667, 95% CI = 0.524, 0.848), dyslipidemia (AHR = 0.561, 95% CI = 0.410, 0.768), and cardiovascular disease (AHR = 0.681, 95% CI = 0.494, 0.938).

CONCLUSION

The median time to initial optimal glycemic control in type 2 diabetes Mellitus patients in this study was short. Age between 50 and 59 years and 60-69, diabetes neuropathy, hypertension, dyslipidemia, and cardiovascular disease were predictor's of time to first glycemic control. Therefore, health care providers should pay extra attention for patients who are aged and who have complications or co-morbidities.

Glycemic control and its associated factors among adult diabetic patients in Southern Ethiopia: a cross-sectional study

Background

Diabetes mellitus is a group of common metabolic disorders that share the phenotype of hyperglycemia. Chronic hyperglycemia causes vascular complications, mortality, and life-threatening disabilities in low-income countries including Ethiopia. Glycemic control status in diabetic patients is crucial to maintain the blood glucose level at the optimal level and to reduce the risk of diabetes-related complications and mortality. However, there is limited data on poor glycemic control status and its associated factors among diabetic patients in southern Ethiopia, particularly in the study area. Thus, this study aimed to determine glycemic control status and its associated factors using glycated hemoglobin among adult diabetic patients at Nigist Elleni Mohammad Memorial Referral Hospital, Hossana, southern Ethiopia.

Materials and methods

A facility-based cross-sectional study was conducted from May 1 to June 30, 2020. A systematic random sampling technique was used to recruit 307 diabetic patients at follow-up. Interviewer administered questionnaire was used to collect data on sociodemographic, clinical, and behavioral characteristics. Five milliliters of venous blood samples were collected to determine lipid profiles and hemoglobin A1C. Lipid profiles and hemoglobin A1C were measured by Cobas c311 analyzer. The data were analyzed by SPSS version 20. Bivariable and multivariable logistic regression were used to determine associated factors with poor glycemic control status. P-value <0.05 was considered statistically significant.

Result

The overall prevalence of poor glycemic control among the study participants based on hemoglobin A1C ≥7% was 82.4%. Having a history of diabetic complications (AOR: 7.09, 95%CI: 1.72-29.16), duration of diabetes ≥7 years (AOR: 4.09, 95%CI: 1.38-12.08), insulin and oral hypoglycemic agents (AOR: 0.106 95%CI: 0.02-0.44), lack of self-glucose monitoring (AOR: 8.27, 95%CI: 1.61-42.46), lack of physical exercise (AOR: 5.5, 95%CI: 1.6-18.9) and dyslipidemia (AOR: 2.74, 95%CI: 1.12-6.66) were significantly associated with poor glycemic control.

Conclusion

A high prevalence of poor glycemic control status (82.4%) was observed among diabetic patients in this study area, and disease-related factors like duration of diabetes, complication, treatment type and lack of self-glucose monitoring, physical exercise, and dyslipidemia were identified as factors significantly associated with poor glycemic control status. The finding of the current study should be taken into account to conduct a strategic and timely intervention on significantly associated factors to delay diabetic complications and to improve the health outcome of diabetic patients. Routine screening and monitoring of dyslipidemia and providing health education on behavioral factors were the necessary measures that should be conducted to reduce the burden of poor glycemic control status among diabetic patients.

Determinants of poor glycemic control among type 2 diabetes in Ethiopia: a systematic review and meta-analysis

Introduction

Prior primary studies have examined the prevalence and factors associated with glycaemic control among patients with type 2 diabetes mellitus, but studies with evidence-based synthesis of the primary data remained unknown. Hence, we aimed to determine the prevalence of poor glycemic control and identify determinants of poor glycemic control in patients with type 2 diabetes in Ethiopia.

Methods

We performed searches in the online databases of PubMed, Google Scholar, Scopus, Science Direct, and the Cochrane Library. Microsoft Excel was used to extract data, and STATA statistical software (v. 16) was used for analysis. Publication bias was explored by forest plots, Begg's rank test, and Egger's regression test. To check for heterogeneity, I2 was computed. Subgroup analysis was conducted based on region and publication year. In addition, the pooled odds ratio for associated factors was calculated.

Results

Out of 1,045 studies assessed, 23 studies were included fulfilling our inclusion criteria. In all, 6,643 individuals were enrolled in the study. It was estimated that 61.11% of type 2 diabetes patients had poor glycemic control (95% CI, 57.14-65.19). The subgroup analysis by study region and publication year revealed that the highest prevalence was observed in the Addis Ababa region (68.57%) and studies published before 2019 (61.76%), respectively. Poor glycemic control was associated with older age > 50 years (AOR = 2.12; 95% CI: 1.27-2.97), not attending formal education (AOR = 3.60; 95% CI: 2.75, 4.46), having diabetes for longer duration (10 years; AOR = 2.57; 95% CI: 1.65-3.49), having comorbidity (AOR = 2.43; 95% CI: 2.05-2.80), and low adherence to diabetes management (AOR = 3.67; 95% CI: 2.41-4.92).

Conclusion

Our findings indicate a high prevalence of poor glycemic control among people with type 2 diabetes in Ethiopia. Being older, not attending formal education, having a longer duration of diabetes, having comorbidity, and having low adherence to diabetes management were all associated. Therefore, we recommend health organizations implement measures to monitor and control patients' blood glucose levels. Patient education and training of healthcare professionals could serve as a short-term strategy to achieve adequate glycemic control.

Systematic review registration

PROSPERO, identifier CRD42022349792, https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022349792.

Frequency and correlates of poor glycemic control in patients with type 2 diabetes at Jimma Medical Centre, Ethiopia: a cross-sectional study

Introduction

the majority of studies in Ethiopia determine the prevalence of glycemic control employed by fasting blood sugar (FBS), which is impacted by a variety of factors. Hence, the purpose of this study was to assess the status of glycemic control using HbA1c and its correlates in patients with type 2 diabetes in Southwest Ethiopia.

Methods

a cross-sectional study was employed among 124 T2 diabetes mellitus (DM) patients at Jimma Medical Center (JMC), Southwest Ethiopia. HbA1c and FBS were estimated using the Cobas 6000 analyzer. The body mass index (BMI) and waist-to-hip ratio were calculated as the standard formula. Data were analyzed by SPSS version 25. Logistic regression analysis was employed to identify independent risk factors associated with poor glycemic control of DM patients.

Results

males comprised 63.7% (n=79) of the total respondents. The mean age of aOR: 2.21, 95% CI 1.13, 4.34; p = 0.01f participants was 51.84 ± 11.6 years; 60.5% (n=75) of T2 DM patients were in poor glycemic control (HbA1c ≥ 7%). In multivariate logistic regression analysis, BMI of ≥ 30, (aOR: 2.21, 95% CI 1.13, 4.34) increased waist-to-hip ratio (aOR: 1.63, 95% CI 0.82, 2.18), high systolic blood pressure (aOR: 1.52, 95% CI 1.11, 6.23), high FBS (aOR: 1.61, 95% CI 1.00, 4.12), and longer duration of DM (aOR: 1.23, 95% CI 0.87, 1.88) were associated with poor glycemic control.

Conclusion

the level of poor glycemic control in the study population is high. Obesity and/or overweight, central obesity, systolic hypertension, and fasting blood sugar levels were all associated with poor glycemic control in T2 DM patients.

Regional prevalence of hypertension among people diagnosed with diabetes in Africa, a systematic review and meta-analysis

Hypertension and diabetes comorbidity can increase healthcare expenditure and the risk of coronary heart disease. We conducted a systematic review and meta-analysis to estimate the prevalence of hypertension among people with diabetes in African countries. We searched EMBASE, PubMed and HINARI databases from inception to March 2023. Cross-sectional studies reporting the prevalence of hypertension among people with diabetes and published in English in Africa were eligible for inclusion. The cross-sectional study design component of the mixed method appraisal tool was used to assess the quality of the included studies. We quantified the overall and regional prevalence of hypertension among people with diabetes using random-effects meta-analysis. We assessed heterogeneity and publication bias using I2 statistics and funnel plots. Out of 3815 articles retrieved from the various databases, 41 met the inclusion criteria with sample sizes ranging from 80 to 116726. The mean age was 58 years (± 11) and 56% were women. The pooled prevalence of hypertension in people diagnosed with diabetes was 58.1% [95% CI: 52.0% - 63.2%]. By region, Central Africa had the highest hypertension prevalence; 77.6% [95% CI: 53.0% - 91.4%], Southern Africa 69.1% [95% CI: 59.8% - 77.1%;], North Africa 63.4% [95% CI: 37.1% - 69.1%;], West Africa 51.5% [95% CI: 41.8% - 61.1%] and East Africa 53.0% [95% CI: 45.8% - 59.1%]. Increasing age, being overweight/obese, being employed, longer duration of diabetes, urban residence, and male sex were reported to be associated with a higher likelihood of developing hypertension. The high prevalence of hypertension among people with diabetes in Africa highlights the critical need for an integrated differentiated service delivery to improve and strengthen primary care and prevent cardiovascular disease. Findings from this meta-analysis may inform the delivery of interventions to prevent premature cardiovascular disease deaths among persons in the region.

Prevalence and determinants of poor glycaemic control in individuals aged between 18-60 years, at a regional hospital in KwaZulu-Natal Province, South Africa- a cross sectional study

Background

Achieving optimal blood glucose control is imperative for preventing diabetes related complications and negative socio-economic consequences associated with them.

Objectives

The aim of the study was to determine the prevalence and determinants of poor glycaemic control amongst type II diabetic outpatients presenting at a regional semi-rural hospital in eThekwini district, Kwa-Zulu Natal.

Methods

An observational, analytic cross-sectional study was conducted amongst 384 systematically sampled type 2 diabetes patients. Data were collected by an interviewer administered questionnaire, clinical record review and anthropometric measurements. Bivariate and multivariate analyses were performed.

Results

Ninety one percent of the study population (349/384) had poorly controlled diabetes. Amongst uncontrolled diabetics, 80% (n=281) were older than 35 years' age group; 58% (n= 203) were male; 85% (n=295) completed primary school education and 93% (n=324) were overweight. Patients that were 35 years and older, female, employed, had a high body mass index, were on oral hypoglycaemic and/or insulin in combination, and receiving treatment longer than 3 years, had an increased odd of uncontrolled diabetes. Being female and receiving oral hypoglycaemic and/or insulin were significantly associated with poor blood glucose control.

Conclusion

Patient that were female overweight, having a lower level of education, and greater than three-year duration of medication and on oral hypoglycaemic agent and/or insulin were more likely to have poor blood glucose control. These factors should serve as early identifiers of potential poor control and an alert clinician to adopt a more active approach to optimize treatment.

HbA1c control in type 2 diabetes mellitus patients with coronary artery disease: a retrospective study in a tertiary hospital in South Africa

Background

Type 2 diabetes mellitus (T2DM) patients with coronary artery disease (CAD) have an increased risk of recurrent cardiovascular events. These patients require optimal glucose control to prevent the progression of atherosclerotic cardiovascular disease (ASCVD). Contemporary guidelines recommend an HbA1c ≤7% to mitigate this risk. The aim of this study was to evaluate HbA1c control in T2DM patients with angiographically proven ASCVD.

Methods

We conducted a cross-sectional, retrospective study on consecutive T2DM patients with acute and chronic coronary syndromes managed in a tertiary academic hospital in South Africa. Glycaemic control was assessed by evaluating the glycated haemoglobin (HbA1c) level measured at index presentation with acute and chronic coronary syndromes and during the most recent follow-up visit.

Results

The study population comprised 262 T2DM patients with a mean age of 61.3 ± 10.4 years. At index presentation, 110 (42.0%) T2DM patients presented with ST-segment elevation myocardial infarction, 69 (26.3%) had non-ST-segment elevation myocardial infarction, 43 (16.4%) had unstable angina, and 40 (15.3%) had stable angina. After a median duration of 16.5 months (IQR: 7-29), 28.7% of the study participants had an HbA1c ≤7%. On multivariable logistic regression analysis, females were less likely to have poor glycaemic control (HbA1c above 7%) [odds ratio (OR): 0.42, 95% confidence interval (CI): 0.19-0.95, p=0.038]. Also, T2DM patients prescribed metformin monotherapy (OR: 0.34, 95% CI: 0.14-0.82, p=0.017) and patients with ST-segment depression on the electrocardiogram (OR: 0.39, 95% CI: 0.16-0.96, p=0.041) were less likely to have poor glycaemic control.

Conclusion

After a median duration of 16.5 months, only 28.7% of T2DM patients with CAD had an HbA1c ≤7%. This finding underscores the substantial unmet need for optimal diabetes control in this very high-risk group.

Poor glycemic control and associated factors among patients with type 2 diabetes mellitus: a cross-sectional study

Glycemic control is of paramount importance in care and management for patients with type 2 diabetes mellitus (T2DM). Poor glycemic control is a major health problem that greatly contributes to the development of diabetes related complications. This study aims to assess the prevalence of poor glycemic control and associated factors among outpatients with T2DM attending diabetes clinic at Amana Regional Referral Hospital in Dar-es-salaam, Tanzania from December 2021 to September 2022. A face to face interviewer semi-structured questionnaire was administered during data collection. Binary logistic regression under multivariable analysis was used to determine the independent predictors of poor glycemic control. A total of 248 patients with T2DM were included in the analysis with mean age of 59.8 ± 12.1 years. The mean fasting blood glucose was 166.9 ± 60.8 mg/dL. The prevalence of poor glycemic control was 66.1% (fasting blood glucose > 130 mg/dL or < 70 mg/dL). Failure to adhere to regular follow-up (AOR = 7.53, 95% CI = 2.34-19.73, p < 0.001) and alcoholism (AOR = 4.71, 95% CI = 1.08-20.59, p = 0.040) were the independent predictors of poor glycemic control. The prevalence of poor glycemic control observed in this study was significantly high. Emphasis should be placed on ensuring that patients have regular follow-up for their diabetes clinics and they should also continue modifying some of lifestyle behaviors including refraining from alcoholism, this can help them to have good glycemic control.

Determinants of poor glycemic control among type 2 diabetes mellitus patients at University of Gondar Comprehensive Specialized Hospital, Northwest Ethiopia: Unmatched case-control study

BACKGROUND

Poor glycemic control is one of the most determinant factors for type 2 diabetes-related morbidity and mortality. The proportion of type 2 diabetes mellitus patients with poor glycemic control remains high. Yet evidence on factors contributing to poor glycemic control remains scarce. The aim of this study is to identify determinants of poor glycemic control among type 2 diabetes mellitus patients at a diabetes mellitus clinic in University of Gondar Comprehensive Specialized Hospital, Northwest Ethiopia Determinants of Poor Glycemic Control among Type 2 Diabetes mellitus Patients at University of Gondar Comprehensive Specialized Hospital, Northwest Ethiopia: Unmatched Case-Control Study.

METHODS

A hospital-based case-control study was conducted from June to September 2020. Using convenience sampling techniques, a total of 90 cases and 90 controls with type 2 diabetes were recruited. The data were entered into Epidata version 4.6.0.2 and analyzed by Stata version 14. A multivariable logistic regression analysis was performed to assess the association between independent variables and glycemic control. Both 95% CI and p-value<0.05 were used to determine the level and significance, respectively.

RESULTS

The mean age ( ± standard deviations) for the cases and controls were 57.55± 10.42 and 61.03± 8.93% respectively. The determinants of poor glycemic control were age (Adjusted odd ratio (AOR)= 0.08; 95% CI= 0.02-0.33), inadequate physical exercise (AOR = 5.05; 95% CI = 1.99-11.98), presence of comorbidities (AOR = 5.50; 95% CI = 2.06-14.66), non-adherence to anti-diabetes medications (AOR= 2.76; 95% CI= 1.19-6.40), persistent proteinuria (AOR=4.95; 95% CI=1.83-13.36) and high-density lipoprotein less than 40 mg/dl (AOR=3.08; 95% CI= 1.30-7.31).

CONCLUSIONS

Age less than 65 years, inadequate physical exercise, presence of comorbidities, non-adherence to anti-diabetes medications, persistent proteinuria, and high-density lipoprotein less than 40 mg/dl were the determinants of poor glycemic control. Therefore, targeted educational and behavioral modification programs on adequate exercise and medication adherence should be routinely practiced. Furthermore, early guideline-based screening and treatment of comorbidities and complications is required to effectively manage diabetes mellitus.

Prevalence of Glycemic Control and Factors Associated With Poor Glycemic Control: A Systematic Review and Meta-analysis

The primary method for preventing health and health-related problems in diabetic people is glycemic control. Numerous studies have documented the importance of glycemic control and the factors that influence it. However, the results are dispersed. This study sought to identify the prevalence of poor glycemic control and associated factors in Ethiopia. Findings will be crucial to reduce the burden of poor glycemic control. Comprehensive search was performed from databases: PubMed, Global Health, CINAHL, IRIS, and FSTA. Gray literature sources were also explored. This document was prepared based on the PRISMA flowchart. The protocol is registered in PROSPERO (ID: CRD42022296583). STATA software was used for data analyses and I2 test with Cochrane Q statistics, and forest plot were used to verify heterogeneity. When the I2 value was higher than 50% and the p-value was 0.05, heterogeneity was deemed significant. To confirm publication bias, a funnel plot with an Egger's regression test was performed. The factors related to poor glycemic control were reported using pooled odds ratios (POR) and a 95% confidence interval. In this study, 46 papers totaling 15 457 people were used to calculate the pooled estimates. It was determined that 32.6% (95% CI: 28.3, 36.9) and 61.92% (95% CI: 57.92, 65.92) of the subjects, respectively, had good and poor glycemic control. Being male protected against poor glycemic control, while poor diet adherence, lack of exercise, poor adherence to anti-diabetic medications, and smoking increased the likelihood of poor glycemic control. Lack of formal education, no family history of diabetes, lack of glucometer for blood glucose monitoring, comorbidity, being overweight and prolonged length of stay with diabetes all contributed to poor glycemic control. Ethiopia had a fairly high rate of poor glycemic control. The main determinants are lifestyle factors. Therefore, it is important to focus on behavioral interventions.

Medication adherence and its impact on glycemic control in type 2 diabetes mellitus patients with comorbidity: A multicenter cross-sectional study in Northwest Ethiopia

BACKGROUND

Medication nonadherence in patients with chronic diseases, particularly in type 2 diabetes mellitus (T2DM) with comorbidity, has continued to be the cause of treatment failure. The current study assessed medication adherence and its impact on glycemic control in T2DM patients with comorbidity.

METHODS

An institutional-based multicenter cross-sectional study was conducted among T2DM patients with comorbidity at the selected hospitals in Northwest Ethiopia. Medication adherence was measured using a structured questionnaire of the General Medication Adherence Scale (GMAS). A logistic regression model was used to identify predictors of the level of medication adherence and glycemic control. P < 0.05 at 95% confidence interval (CI) was statistically significant.

RESULTS

A total of 403 samples were included in the final study. This study showed that more than three-fourths (76.9%) of the participants were under a low level of medication adherence. Source of medication cost coverage [AOR = 10.593, 95% CI (2.628-41.835; P = 0.003], monthly income (P < 0.00), self-monitoring of blood glucose (SMBG) practice [AOR = 0.266, 95% CI (0.117-0.604); P = 0.002], number of medications [AOR = 0.068, 95% CI (0.004-0.813); P = 0.014] and medical conditions [AOR = 0.307, 95% CI (0.026-0.437); P = 0.018] were found to be significant predictors of medication adherence. Significantly, majority (74.7%) of participants had poor levels of glycemic control. Patients who had a high level of medication adherence [AOR = 0.003, 95% CI (0.000-0.113); P = 0.002] were found less likely to have poor glycemic control compared with patients who were low adherent to their medications.

CONCLUSION

The current study concluded that medication adherence was low and significantly associated with poor glycemic control. Number of medical conditions and medications were found to be associated with medication adherence. Management interventions of T2DM patients with comorbidity should focus on the improvement of medication adherence.

Glycaemic control among type 2 diabetes patients in sub-Saharan Africa from 2012 to 2022: a systematic review and meta-analysis

BACKGROUND

There is an increased burden of diabetes globally including in sub-Saharan Africa. The literature shows that glycaemic control among type 2 diabetes patients is poor in most countries in sub-Saharan Africa. Understanding the factors influencing glycaemic control in this region is therefore important to develop interventions to optimize glycaemic control. We carried out a systematic review to determine the prevalence and factors associated with glycaemic control in sub-Saharan Africa to inform the development of a glycaemic control framework in the Democratic Republic of the Congo.

METHODS

We searched five databases (African Index Medicus, Africa-Wide Information, Global Health, PubMed, and Web of Science) using the following search terms: type-2 diabetes, glycaemic control, and sub-Saharan Africa. Only peer-reviewed articles from January 2012 to May 2022 were eligible for this review. Two reviewers, independently, selected articles, assessed their methodological quality using Joanna Briggs checklists, and extracted data. A meta-analysis was performed to estimate the prevalence of glycaemic control. Factors associated with glycaemic control were presented as a narrative synthesis due to heterogeneity as assessed by the I2.

RESULTS

A total of 74 studies, involving 21,133 participants were included in the review. The pooled prevalence of good glycaemic control was 30% (95% CI:27.6-32.9). The glycaemic control prevalence ranged from 10-60%. Younger and older age, gender, lower income, absence of health insurance, low level of education, place of residence, family history of diabetes, longer duration of diabetes, pill burden, treatment regimen, side effects, use of statins or antihypertensives, alcohol consumption, smoking, presence of comorbidities/complications, and poor management were associated with poor glycaemic control. On the other hand, positive perceived family support, adequate coping strategies, high diabetes health literacy, dietary adherence, exercise practice, attendance to follow-up, and medication adherence were associated with good glycaemic control.

CONCLUSION

Suboptimal glycaemic control is pervasive among patients with type-2 diabetes in sub-Saharan Africa and poses a significant public health challenge. While urgent interventions are required to optimize glycaemic control in this region, these should consider sociodemographic, lifestyle, clinical, and treatment-related factors. This systematic review and meta-analysis protocol is registered in PROSPERO under CRD 42021237941.

Rate of glycaemic control and associated factors in patients with type 2 diabetes mellitus treated with insulin-based therapy at selected hospitals in Northwest Ethiopia: a multicentre cross-sectional study

OBJECTIVES

This study was aimed to determine the level of glycaemic control and associated factors in patients with type 2 diabetes mellitus (T2DM) treated with insulin-based therapy.

DESIGNS

Institutional-based multicentre cross-sectional study design was employed to conduct this study.

SETTINGS

The diabetes follow-up clinics of selected hospitals in Northwest Ethiopia.

PARTICIPANTS

Adult patients with T2DM treated with insulin-based therapy at the selected hospitals who met the eligibility criteria were the study participants.

MAIN OUTCOME MEASURES

Good glycaemic control; when fasting blood glucose (FBG) level ranged from 70 to 130 mg/dL, and FBG <70 and >130 mg/dL was considered poor glycaemic control. A logistic regression model was used to identify determinants of poor glycaemic control. A p<0.05 at 95% CI was statistically significant.

RESULTS

Of 403 study participants, 54.8% were males with a mean age of 55.03±10.8 years. Though patients with T2DM were treated with insulin-based therapy, most of the participants (72.5%) could not achieve the target FBG. The overall mean FBG was 177.1±54.3, and far from the target glucose level. Patients who could not practise self-monitoring of blood glucose were found more likely to have poor glycaemic control compared with those who practised self-monitoring (p<0.001). Whereas patients who had a normal body mass index (p=0.011) and who were treated with premixed insulin-based therapy (p=0.04) were found less likely to have poor glycaemic control compared with patients with obesity and who received NPH insulin based-regimens, respectively.

CONCLUSION

This study demonstrated that a significant proportion of the study samples could not achieve glycaemic targets and the average blood glucose was far higher than the recommended glycaemic target level. Insulin initiation and titration, considering the determinants of glycaemic control, could be recommended to achieve target glycaemic levels.

Poor glycemic control, cardiovascular disease risk factors and their clustering among patients with type 2 diabetes mellitus: A cross-sectional study from Nepal

Background

Cardiovascular disease (CVD) is the most common complication of diabetes mellitus (DM). To prevent morbidity and mortality among patients with type 2 diabetes mellitus (T2DM), optimization of glycemic status and minimizing CVD risk factors is essential. As Nepal has limited data on these CVD risk parameters, we assessed the prevalence of poor glycemic control, CVD risk factors, and their clustering among patients with T2DM.

Methods

Using a cross-sectional study design, we collected data of 366 patients with T2DM. We applied a multistage cluster sampling technique and used the WHO STEPS tools. Binary logistic and Poisson regression was applied to calculate odds and prevalence ratio of clustering of risk factors, considering P< 0.05 statistically significant.

Results

The mean age of participants was 54.5±10.7 years and 208 (57%) were male. The prevalence of poor glycemic control was 66.4% (95% C.I: 61.5–71.2). The prevalence of smoking, alcohol users, inadequate fruit and vegetables intake and physical inactivity were 18% (95% C.I:14 to 21.9), 14.8% (95% C.I:11.1 to 18.4), 98.1% (95% C.I: 96.7–99.4), and 9.8% (95% C.I:6.7–12.8), respectively. Overall, 47.3% (95% C.I: 42.1–52.4) were overweight and obese, 59% (95% C.I: 52.9–63) were hypertensive, and 68% (95% C.I: 63.2–72.7) had dyslipidemia. Clustering of two, three, four, five and more than five risk factors was 12.6%, 30%, 30%,19%, and 8.7%, respectively. Four or more risk factors clustering was significantly associated with gender, age, level of education, T2DM duration, and use of medication. Risk factors clustering was significantly higher among males and users of anti-diabetic medications with prevalence ratio of 1.14 (95% C.I:1.05–1.23) and 1.09 (95% C.I: 1.09–1.18)], respectively.

Conclusions

The majority of the patients with T2DM had poor glycemic control and CVD risk factors. Policies and programs focused on the prevention and better management of T2DM and CVD risk factors should be implemented to reduce mortality in Nepal.

Self-care practice and glycemic Control among type 2 diabetes patients on follow up in a developing country: a prospective observational study

Purpose

The main goal of managing diabetes is to achieve glycemic control. However, the glycemic level of most diabetic patients is shown to be poorly controlled mainly due to poor adherence to self-care practices. This study aims to assess the level of self-care practice and glycemic control among type 2 diabetes patients on follow up in a resource limited country.

Methods

A four-month prospective observational study was conducted among type 2 diabetes patients from February 1 to May 30, 2021. Data was collected using a data abstraction checklist and structured questionnaire. The data was entered into Epidata version 4.4.6 and analyzed with SPSS version 26. Glycemic control and its predictors were determined using binary logistic regression. P-value less than 0.05 was considered as statistically significant.

Results

A total of 138 patients were included in the study. Nearly three-fourths (74.6%) of patients had poor glycemic control and the majority of patients had poor self-care practice. 78.3%, 98.6%, 96.4%, and 55.8% of patients had poor adherence to diet, exercise, self-monitoring of blood glucose, and medications respectively. Importantly, 85(79%), 102(75%), 99(74.4%), and 65(84.4%) patients with poor adherence to diet, physical activity, self-monitoring of blood glucose, and antidiabetic medications had poor glycemic control. On multivariate logistic regression, BMI (AOR 4.1, CI:1.20-14.11, p = 0.024) and drug adherence (AOR 3.08, CI:1.22-7.08, p = 0.017) were factors associated with poor glycemic control.

Conclusions

A higher proportion of patients had low-level of self-care practice and poor glycemic control. This highlights the need to improve patients' awareness about the importance of self-care practice to maintain good glycemic control and prevent adverse outcomes associated with the disease.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40200-022-00995-4.

Knowledge of the Therapeutic Goals of Diabetes Care among Patients with Type 2 Diabetes at a Tertiary Hospital in Ethiopia

Background

A comprehensive cardiovascular risk control reduces diabetes-associated complications but achieving the triplet goals (blood glucose, blood pressure (BP), and low-density lipoprotein (LDL-C)) remains a clinical challenge. Patients' knowledge of these diabetes therapeutic goals has been shown to improve glycemic control. However, this is not well studied in Ethiopia.

Methods

A cross-sectional study was conducted from March to June 2020 in Tikur Anbessa Specialized Hospital among randomly selected 419 patients with type 2 diabetes. Data was collected using a pretested, structured questionnaire. A multivariable binary logistic regression was fitted to identify determinants of knowledge.

Results

The mean age (±SD) of study participants was 57.4 (±10.8) years and the median duration (IQR) of diabetes was 12 (7, 20) years. A quarter of them achieved fasting glycemic control, a fifth of them attained the A1c goal and only 3% achieved the triple targets. Patients who reported knowing their target goals for BP, fasting blood sugar (FBS), A1C, and LDL-C were 79.5, 77.3, 11.7, and 7.2% respectively. The factors associated with knowledge of the therapeutic goals were longer diabetes duration, increased household income, age, being divorced as compared to married, having no formal education, and primary education.

Conclusion

The majority of participants knew their BP and FBS targets while only a minority understood their A1c and LDL-C targets. It highlighted the need for the provision of patient-centered diabetes education to improve knowledge of the therapeutic targets.

Evaluation of glycemic control and related factors among outpatients with type 2 diabetes at Tikur Anbessa Specialized Hospital, Addis Ababa, Ethiopia: a cross-sectional study

BACKGROUND

The goals of glycemic management for patients with diabetes are to prevent or delay complications and optimize quality of life. However, in clinical practice, the recommended glycemic control target is difficult to achieve. Therefore, it is important to identify factors that influence the outcomes of glycemia to improve the quality of diabetic management. The study aimed to evaluate the level and factors associated with glycemic control among type 2 diabetic outpatients at Tikur Anbessa Specialized Hospital, Addis Ababa, Ethiopia.

METHODS

A hospital-based cross-sectional study was conducted among systematically selected 325 patients with type 2 diabetes who attended diabetic clinics at Tikur Anbessa Specialized Hospital. Pretested, structured, and interviewer-administered questionnaires were used to collect sociodemographic and diabetes-related information from March 1 to May 30, 2021. HbA1c was used to assess glycemic control according to the HbA1c target of < 7% ('good' control) as recommended by the American Diabetes Association for non-pregnant adults. The HbA1c level in the range of 7-8% was defined as 'inadequate' control and 'poor' at levels > 8%. Data entry and analysis were performed using SPSS v26. Multivariate logistic regression analysis was used to identify determinants of glycemic control.

RESULTS

The median level of HbA1c of the participants was 8.4% (IQR 6.8-10.1). And approximately three-quarters (73.8%) of the patients had inadequate and poor glycemic control (HbA1c ≥ 7%). Older age (AOR: 2.46, 95% CI: 1.28-6.01), DM duration of > 10 years (AOR: 3.15, 95% CI: 2.22-6.54), insulin therapy (AOR: 3.07, 95% CI: 2.10-6.12), poor diet compliance (AOR: 1.97, 95% CI: 1.28-3.52) and failure to set goals for glycemic control (AOR: 3.42, 95% CI: 2.17-5.97) were factors associated with inadequate and poor glycemic control.

CONCLUSIONS

The study revealed that a significant number of diabetic patients had inadequate and poor glycemic control levels. And this was associated with older age, longer duration of DM, insulin therapy, poor diet compliance, and failure to set control goals. This requires a focus on the associated factors identified and tailored management mechanisms to maintain good glycemic control.

Poor glycemic control and its associated factors among diabetes patients attending public hospitals in West Shewa Zone, Oromia, Ethiopia: An Institutional based cross-sectional study

Purpose

Diabetes mellitus (DM) is increasing at an alarming rate throughout the world and its complications of has become a major public health concern in all countries. Glycemic control is the most important predictor for DM related complications and deaths. However information on glycemic control remains scarce in Ethiopia including our study area. Hence, the aim of this study was to assess the magnitude and factors associated with poor glycemic control among diabetic outpatients at West Shewa public Hospitals, Ethiopia.

Methods

A facility-based cross-sectional study was conducted from June 01 to September 30, 2020. Poor glycemic control was assessed by glycated hemoglobin level and a systematic random sampling method was employed to select participants. An interviewer-administered structured questionnaire was used and the data entered into Epi data version 3.1 and exported into SPSS version 22 for analysis. Logistic regression was conducted to identify predictors of poor glycemic control. A p-value of <0.05 was considered statistically significant.

Results

A total of 390 participants were involved in the study with mean age of 46.45 (±15.6) years. The study finding showed that the prevalence of poor glycemic control was found to be 63.8%. Age of ≥50 years (AOR = 2.77; 95% CI: 0.15,0.85), being single (AOR = 2.55; 95% CI: 0.179,.857), having high low-density lipoprotein cholesterol (AOR = 3.44; 95% CI: 1.65, 7.12), being female gender (AOR = 2.4; 95%CI: 0.31,0.816), alcohol intake (AOR = 1.88; 95% CI: 1.135, 3.1) and presence of diabetic peripheral neuropathy (AOR = 1.24; 1.1,1.39) were associated with poor glycemic control.

Conclusion

About two-thirds of participants had poor blood glucose control. Increased age, high low-density lipoprotein cholesterol, family history of diabetes, being single, being female, diabetic peripheral neuropathy and alcohol intake were associated with poor glycemic control. Hence, effort should be made towards reducing these factors among DM patients by the concerned body.

Diabetic foot ulcer disease in African continent: 'From clinical care to implementation' - Review of diabetic foot in last 60 years - 1960 to 2020

The prevalence of diabetes mellitus is increasing globally and the greatest potential increases in diabetes will occur in Africa. Data suggest that these increases is associated with rapid demographic, sociocultural and economic transitions. There will be a parallel increase in the complications of diabetes and among the various complications those related to diabetic foot disease are associated with the highest morbidity and mortality. Diabetic Peripheral neuropathy (DPN) is the most common cause of diabetic foot complications in African countries; however, peripheral arterial disease (PAD) appears to increase, possibly a result of rising urbanization. Search done for the past six decades (1960 to 2020) on all foot complications. Rates of complications of diabetic foot in last six decades varied by country as follow: DPN: 4-90%; PAD: 0-77%; foot ulcers: 4-61%; amputation rates: 3-61% and high mortality rates reaching to 55%, patients who presented late with infection and gangrene. Educational and prevention programmes are required to curb the growing complications of diabetic foot ulcers in Africa among patients and health care workers. Secondly, it is imperative that governments across the African continent recognise the clinical and public health implications of diabetic foot disease in persons with diabetes.

Association of glycemic control and anthropometric measurement among type 2 diabetes mellitus: a cross-sectional study

Introduction

Maintaining good glycemic control is the main therapeutic target for diabetes mellitus (DM) patients. Nevertheless, due to complex factors, the majority of patients worldwide persist poorly controlled. Hence the study was conducted to determine the association of anthropometric measurement and other factors with glycemic control among type 2 DM patients.

Methods

An institutional-based cross-sectional study was conducted among 366 type 2 DM patients from October-1 to November 30/2019. Data were collected by a pre-tested structured questionnaire and data abstraction format. The collected data were edited in Epi-data-4.4.1.0 and exported to SPSS-25 for analysis. The degree of association was assessed using logistic regression analysis and expressed in terms of p value and odds ratio with a 95%CI. p value < 0.05 was considered statistically significant.

Results

Of the total 366 participants, (66.1%) had poor glycemic control. Increased waist circumference (AOR 2.37, 95% CI 1.28-4.40 for overweight and AOR 3.31, 95% CI 1.28-8.58 for obesity), long duration of DM (AOR 2.12, 95% CI 1.14-3.95 for 5-10 years and AOR 5.67, 95% CI 1.76-11.30 for > 10 years), occupation (AOR 3.74, 95% CI 1.94-7.23 for government employee and AOR 4.90, 95% CI 2.19-10.94 for private employee), and family history of DM (AOR 1.93, 95% CI 1.08-3.43), were significantly associated with poor glycemic control.

Conclusion

Nearly two-thirds of study participants had poor glycemic control. Increased waist circumference, long duration of DM, occupational status, and family history of DM were independently associated with poor glycemic control. Therefore, type 2 DM patients with these identified factors should be strictly monitored to maintain good glycemic control.

Prevalence and determinants of poor glycaemic control amongst patients with diabetes followed at Vanga Evangelical Hospital, Democratic Republic of the Congo

Background

The prevalence of diabetes mellitus is increasing dramatically in developing countries, where diabetic patients usually present with poor glycaemic control, leading to complications and worsening the prognosis.

Aim

The aim of this study was to determine the extent of poor glycaemic control and its determinants in diabetic patients.

Setting

The study was conducted in a rural area of the province of Kwilu, Democratic Republic of the Congo.

Methods

This research comprised a cross-sectional study involving 300 Type 1 and 2 diabetic patients attending Vanga Evangelical Hospital in the Democratic Republic of the Congo from January 2018 to March 2018. Patients’ sociodemographic, clinical and biological characteristics, accessibility to the health structure and treatment were described. The determinants of poor glycaemic control were identified using multivariate logistic regression at the p < 0.05 level of statistical significance.

Results

The mean age of participants was 46.9 ± 16.3 years, 68.4% were men, and 62.3% had Type 2 diabetes mellitus. Poor glycaemic control was present in 78% of patients. The independent determinants of poor glycaemic control were tobacco use (adjusted odds ratio [aOR]: 2.01 [1.77–5.20], p = 0.015), the presence of comorbidities (aOR: 2.86 [1.95–6.65], p = 0.007), the presence of a factor contributing to hyperglycaemia (aOR: 2.74 [1.83–3.67], p = 0.014), missing scheduled appointments (aOR: 2.59 [1.94–7.13], p = 0.006) and non-adherence to treatment (aOR: 4.09 [1.35–6.39], p = 0.008).

Conclusion

This study shows that more than three-quarters of diabetics undergoing treatment are not controlled, with mainly patient-related factors as the main explanatory factors for this poor glycaemic control. Therefore, the establishment of a therapeutic education programme and wider integration of diabetes care services, mainly at the primary level of the healthcare pyramid, should contribute to improved diabetes treatment.

Magnitude and predictors of poor glycemic control among patients with diabetes attending public hospitals of Western Ethiopia

BACKGROUND

Diabetes is one of the most prevalent non-communicable diseases globally, which rapidly is increasing in developing countries. Ethiopia is also facing growing morbidity and mortality related to diabetes complications. Thus, dealing with glycemic control is essential for controlling the development of devastating acute and chronic complications related to diabetes. Therefore, this study aims to assess the magnitude and predictors of poor glycemic control among diabetic patients in western Ethiopia.

METHODS

The cross-sectional study design was employed on a sample of 423 diabetic patients. A systematic random sampling method was employed. An interviewer-administered structured questionnaire was used. The data entered into Epi data version 3.1 and exported into Statistical Package for the Social Sciences window version 24 for analysis. All variables significant at p-<0.25 in bivariate were entered into multivariate analysis. The multivariable logistic regressions were used to determine predictors' poor glycemic control by considering the Adjusted Odds Ratio at CI 95% and the significance level was set at p <0.05.

RESULTS

The magnitude of poor glycemic control was 64.1%. Being females (AOR = 1.684,95%CI = 1.066,2.662), duration of diabetes >8years (AOR = 2.552,95%CI = 1.397, 4.665), presence of diabetes complication (AOR = 2.806,95%CI = 1.594,4.941), negligence of blood glucose test at home (AOR = 1.720, 95%CI = 1.078, 2.743), poor self-care behavior (AOR = 1.787, 95%CI = 1.083,2.959) and poor self-efficacy (AOR = 1.934, 95%CI = 1.078,3.469) were significant predictors of poor glycemic control.

CONCLUSION

The proportion of poor glycemic control was high which was nearly comparable to that reported from many countries. This could be due to factors that were significantly associated with poor glycemic control like lack of home blood glucose test, increased duration of diabetes, presence of diabetes complications, poor self-efficacy, and poor self-care behaviors. Each were significant independent predictors of poor glycemic control. Thus, we recommend patients with diabetes and health care providers enhancing self-monitoring practices, and preventing potential complications should be a priority concern to improve blood glucose levels. Further studies are also recommended to explore important factors which were not identified by the current study.

Determinants of diabetes ketoacidosis among diabetes mellitus patients at North Wollo and Waghimra zone public hospitals, Amhara region, Northern Ethiopia

BACKGROUND

Diabetes Mellitus (DM) is a metabolic disorder associated with acute and chronic complications. Diabetic ketoacidosis (DKA) is the most serious diabetic emergency in patients with type one and type two diabetes mellitus. It is the leading cause of mortality in children and young adults. Even though the burden of DKA has increased, no research has been conducted on the determinants of Diabetes ketoacidosis in Ethiopia, particularly in the Amhara region. Thus, this study aimed to identify the determinants of diabetes Ketoacidosis among Diabetes Mellitus patients at North Wollo and Waghimra Zone public Hospitals.

METHODS

An institution-based unmatched case-control study design was employed among 408 patients at North Wollo and Waghimra Zone Public Hospitals from March 1st to April 30th, 2020. A consecutive sampling method was used to select study participants. The data were collected using structured interviewer-administered questioners and reviewing of patient charts. The analysis was done using a binary logistic regression model. Then, P-value < 0.05 was considered statistically significant.

RESULT

The mean (±SD) age of the study participants was 46.96 (± 15.175 SD) years. Irregular follow-up in diabetes clinic (AOR:4.19, 95% CI: 2.28-7.71), not received diabetic education (AOR: 2.87, 95% CI:1.44-5.72), alcohol drinking (AOR:2.99, 95% CI: 1.46-6.12), discontinuation of medications (AOR: 4.31, 95% CI:1.92-9.68), presence of comorbidity (AOR:2.57, 95% CI: 1.37-4.84), and being type one of diabetes mellitus (AOR: 2.01, 95% CI:1.11-3.63) were determinant factors of diabetic ketoacidosis .

CONCLUSIONS

This study showed that the behavioral and clinical characteristics of diabetic patients were determinant factors of DKA. Follow-up in the diabetic clinic, diabetic education, discontinuation of medications, alcohol drinking, presence of comorbidities, and type of diabetes mellitus were independent determinants of diabetic ketoacidosis.

Glycemic Control of Diabetes Mellitus Patients in Referral Hospitals of Amhara Region, Ethiopia: A Cross-Sectional Study

Background

Glycemic control is the level of glucose in diabetes patient. Evidence regarding glycemic control is scarce in resource-limited settings, and this study was conducted to generate information regarding the prevalence and predictors of glycemic control among diabetes mellitus patients attending their care from the referral hospitals of the Amhara region, Ethiopia.

Methods

A cross-sectional study design was implemented. A simple random sampling technique was used. Data were collected from March 2018 to January 2020. The data were collected using interviews, chart review, and blood samples. Hemoglobin A1c was measured using high-performance liquid chromatography. Data were entered into Epi-info software and analyzed by SPSS software. Descriptive statistics were used to estimate the prevalence of glycemic control; linear regression was used to identify the predictors of HbA1c.

Results

A total of 2554 diabetes patients were included giving for the response rate of 95.83%. The mean age of the study participants was 54.08 years [SD (standard deviation) ± 8.38 years]. The mean HbA1c of the study participants was 7.31% [SD ± 0.94%]. Glycemic control was poor in 55.32% [95% CI: 53.4%-57.25%] of diabetes patients. The glycemic control of diabetes patients was determined by BMI (β 0.1; [95% CI: 0.09-0.1]), type 2 diabetes (β -0.14; [95% CI: -0.11-0.16]), age (β 0.22; [95% CI: 0.02-0.024]), duration of the disease (β 0.04; [95% CI: 0.037-0.042]), the presence of hypertension (β 0.12; [95% CI:0.09-0.16]), regular physical exercise (β -0.06; [95% CI: -0.03-0.09]), medication adherence (β -0.16; [95% CI: -0.14-0.18]), and male (β 0.34; [95% CI: 0.31-.037]).

Conclusion

The glycemic control of diabetes patients was poor, and it needs the attention of decision-makers.

Poor Glycemic Control and the Contributing Factors Among Type 2 Diabetes Mellitus Patients Attending Outpatient Diabetes Clinic at Mbarara Regional Referral Hospital, Uganda

BACKGROUND

Glycemic control is associated with long-term complications in type 2 diabetes management. However, updated reports on glycemic control that are crucial to reducing diabetes mellitus complications remain scarce.

OBJECTIVE

The objective of this study is to evaluate glycemic control and contributing factors among type 2 diabetes mellhitus patients attending the outpatient diabetic clinic at Mbarara Regional Referral Hospital.

METHODS

A cross-sectional study was conducted at Mbarara Regional Referral Hospital outpatient diabetes clinic between July and October 2020. Participants were subjected to a questionnaire-based interview and glycosylated hemoglobin (HbA1C) was determined as a marker of glycemic control among participants. The collected data was entered into and analyzed by Stata version 13. The odds ratio was used to determine the strength of association between variables. The cut-off value for all statistical significance tests was set at p<0.05 with CI of 95%.

RESULTS

A total of 223 participants were interviewed, and the majority (188, 84.3%) had poor glycemic control (HbA1C ≥7%). Importantly, 81.7% (49/60) and 90.0% (99/110) of those who did not adhere to diet and physical exercise recommendations respectively, had poor glycemic control. Multivariate logistic regression revealed that poor glycemic control was more prevalent among participants aged 25-60 years (AOR=4.48, 95%CI: 1.56-14.50, p-value=0.009) and those aged above 60 years (AOR=4.28, 95%CI: 1.18-15.58, p-value= 0.03) compared to the youth, 18-24 years of age.

CONCLUSION

The prevalence of poor glycemic control among type 2 diabetes patients in this study is high and patient's age was identified to be an independent risk factor. We recommend any intervention by the hospital that promotes diabetes education and optimizes lifestyle and medication adherence; ultimately to achieve good glycemic control especially for adult patients.

Antihyperglycemic Activity of TLC Isolates from the Leaves of Aloe megalacantha Baker in Streptozotocin-Induced Diabetic Mice

BACKGROUND

Diabetes mellitus (DM) is a group of metabolic disorders that are characterized by hyperglycemia which results from defects in insulin release or its efficient use by the human body. Although significant progress has been made to manage DM and related complications, it remains a major global health problem. To this end, the search for new antidiabetic drugs from traditionally claimed medicinal plants is important. Aloe megalacantha Baker is an endemic plant used traditionally to treat diabetes in Ethiopia. This study aimed to investigate antidiabetic activity of isolates from the leaf of A. megalacantha Baker in streptozotocin-induced diabetic mice.

METHODS

The exudate of A. megalacantha was collected by cutting the leaves and scraping the yellow sap and then dried at room temperature. The dried exudate was subjected to repeated thin layer chromatographic (TLC) separations using a mixture of solvent system to isolate the major compounds identified on the TLC plate. A single dose of streptozotocin (50 mg/kg) was injected intraperitoneally to overnight fasted mice to induce diabetes. Antidiabetic activity of TLC isolates was assessed by in vivo methods including oral glucose tolerance test, antihyperglycemic and hypoglycemic activity tests.

RESULTS

Three major isolates were obtained from the TLC analysis of the exudate of A. megalacantha. Exudate and TLC isolates were found to be non-toxic up to a dose of 2000 mg/kg. The TLC isolates (Ia and Ib) significantly (p<0.05) reduced blood glucose levels and also increased body weight change of the diabetic mice compared with control groups.

CONCLUSION

The present study demonstrated the ability of the exudate of A. megalacantha and its TLC isolates to significantly decrease blood glucose levels and increase body weights in mice, thus strengthening the claim of its traditional use in DM-related disorders.

Poor Glycemic Control and Its Contributing Factors Among Type 2 Diabetes Patients at Adama Hospital Medical College in East Ethiopia

BACKGROUND

Poor glycemic control is a major public health issue among patients with type 2 diabetes mellitus and a significant risk factor for the progression of diabetic complications. This study aimed to assess the magnitude and contributing factors of poor glycemic control among type 2 diabetes patients on follow-up at Adama Hospital Medical College (AHMC) in East Ethiopia.

METHODS

A cross-sectional study was conducted among 245 type 2 diabetes patients on follow-up at AHMC from March 1 to 30, 2020. All type 2 diabetes patients on follow-up at AHMC and fulfilling the inclusion criteria were included in the study. The data were collected through face-to-face interviews using structured questionnaires and reviewing the patient chart. The data were entered and analyzed using SPSS version 21. The level of significance was declared at a p-value of <0.05.

RESULTS

Of the 245 type 2 diabetes patients included in the study, 157 (64.1%) had poor glycemic control. The factors associated with poor glycemic control were being male (AOR = 2.28, 95% CI [1.24-4.21]), not attending formal education (AOR = 3.12, 95% CI [1.53-6.35]), monthly income of <136 USD (AOR = 2.14, 95% CI [1.17-3.91]), overweight (AOR = 2.60, 95% CI [1.32-5.10]) and obesity (AOR = 3.44, 95% CI [1.44-8.21]), and chewing khat (AOR = 2.77, 95% CI [1.04-7.33]).

CONCLUSION

The proportion of poor glycemic control among type 2 diabetes patients at AHMC was remarkably high. Therefore, more effort should be taken to strengthening and disseminating health education programs for diabetes patients at each follow-up visit on the importance of achieving optimal body weight, avoiding khat chewing, and maintaining regular physical exercise to prevent and mitigate the complications resulting from poor glycemic control.

Factors affecting achievement of glycemic targets among type 2 diabetes patients in South Asia: Analysis of the CARRS trial

OBJECTIVE

To assess the predictors of achieving and maintaining guideline-recommended glycemic control in people with poorly controlled type 2 diabetes.

METHODS

We analyzed data from the Centre for Cardiometabolic Risk Reduction in South Asia (CARRS) Trial (n = 1146), to identify groups that achieved guideline-recommended glycemic control (HbA1c < 7%) and those that remained persistently poorly controlled (HbA1c > 9%) over a median of 28 months of follow-up. We used generalized estimation equations (GEE) analysis for each outcome i.e. achieving guideline-recommended control and persistently poorly controlled and constructed four regression models (demographics, disease-related, self-care, and other risk factors) separately to identify predictors of HbA1c < 7% and HbA1c > 9% at the end of the trial, adjusting for trial group assignment and site.

RESULTS

In the final multivariate model, adherence to prescribed medications (RR: 1.46, 95%CI: 1.09, 1.95), adherence to diet plans (RR: 1.79, 95% CI: 1.43, 2.23) and middle-aged: 50-64 years (RR: 1.32; 95% CI: 1.02-1.71) were associated with achieving guideline-recommended control (HbA1c < 7%). Presence of microvascular complications (RR: 0.70; 95%CI: 0.53-0.92) reduced the probability of achieving guideline-recommended glycemic control (HbA1c 7%). Further, longer duration of diabetes (>15 years), RR: 1.41; 95% CI: 1.15, 1.72, hyperlipidemia, RR: 1.19; 95% CI: 1.06, 1.34 and younger age group (35-49 years vs. >64 years: RR: 0.61; 95% CI: 0.47-0.79) were associated with persistently poor glycemic control (HbA1c > 9%).

CONCLUSION

To achieve and maintain guideline-recommended glycemic control, care delivery models must put additional emphasis and effort on patients with longer disease duration, younger people and those having microvascular complications and hyperlipidemia.

Diabetic Peripheral Neuropathy in Ethiopia: A Systematic Review and Meta-Analysis

BACKGROUND

Currently, diabetic peripheral neuropathy (DPN) is one of the most severe complications of diabetes mellitus (DM). Despite the seriousness of this problem, limited evidence is available on the prevalence of diabetic peripheral neuropathy among patients with diabetes mellitus in Ethiopia. In Ethiopia, there were no updated studies that estimate the national prevalence of DPN. Hence, this systematic review and meta-analysis provided a national prevalence of diabetic peripheral neuropathy among patients with diabetes mellitus in Ethiopia.

METHODS

This study was submitted for registration with the International Prospective Register of Systematic Reviews (PROSPERO) in March 2020 and accepted with the registration number CRD42020173831. Different database searching engines were searched online to retrieve related articles, including PubMed, Scopus, Google Scholar, African Journals Online, World Health Organization (WHO) Afro Library, and Cochrane Review. The reviewers used the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guideline in the reviewing process. In this systematic review and meta-analysis, all published and unpublished articles were analyzed. The reviewers used the random effects model to estimate the pooled prevalence of diabetic peripheral neuropathy among diabetes mellitus patients. The reviewers conducted the statistical analysis using the R version 3.5.3 and RStudio version 1.2.5033 software for Windows. The reviewers evaluated the heterogeneity across the included studies by the inconsistency index (I ²). The reviewers examined the publication bias by the funnel plot.

RESULTS

The search of the databases produced 245 papers. After checking the inclusion and exclusion criteria, 38 articles with 14029 total patients with diabetes mellitus were found suitable for the review. Except for three (retrospective cohort study), all studies were cross-sectional. The overall pooled prevalence of diabetic peripheral neuropathy was 22% (95% CI 18% to 26%). The subgroup analysis of diabetic peripheral neuropathy among patients with diabetes in the different regions was 23% (95% CI 17% to 29%) in Addis Ababa, 27% (95% CI 16% to 38%) in Oromia, 16% (95% CI 14% to 18%) in South nation and nationalities, and 15% (95% CI 6% to 24%) in Amhara.

CONCLUSIONS

More than one-fifth of patients with diabetes have diabetic peripheral neuropathy. According to this study, the prevalence of diabetic peripheral neuropathy in Ethiopia is considerably high. This evidence suggests that attention should be given to patients with diabetes in monitoring patients' blood glucose.

Predictors of Poor Plasma Glucose Maintenance in Type II Diabetic People with Ophthalmic Complication: The Case of Dessie Hospitals in Ethiopia

BACKGROUND

Diabetes mellitus, the commonest metabolic disorder, leads to cardiovascular diseases, neurological problems, kidney injury, and visual disturbances. Such complications can be prevented by maintaining plasma glucose level in the normal range, including ophthalmic complications. Hence, this study intended to pinpoint predictors of poor plasma glucose maintenance in type II DM people with ophthalmic complication.

METHODS

We conducted a cross-sectional survey using simple random sampling approach to recruit participants. An interviewer-based questionnaire was used and ophthalmic complication was determined by visual acuity test. We used statistical package for social sciences version 23 to analyze the data and descriptive statistics were calculated. Predictors were ascertained using multivariable logistic regression at p≤0.05. Besides, AOR with 95% CI was also estimated to show extent of association.

RESULTS

The prevalence of poor plasma glucose maintenance was 65.1% (56.6-73.6). Poor plasma maintenance was predicted by the absence of formal education (OR: 0.67; 0.20-2.23), DM history of family members (OR=4.29; 1.33-13.83), longer duration of diabetes (OR: 3.02; 1.09-8.63), insulin use (OR=10.05; 2.72-52.35), and less physical exercise (OR=2.91; 1.47-5.76).

CONCLUSION

Study subjects with no education, DM history of family members, prolonged DM, insulin medication, and inadequate exercise had higher rate of poor plasma glucose maintenance. Health professionals should educate patients on the importance of self-adherence to plasma glucose monitoring, and encourage them to practice recommended physical activity.

Evaluation of glycemic control status and its associated factors among diabetes patients on follow-up at referral hospitals of Northwest Ethiopia: A cross-sectional study, 2020

INTRODUCTION

Diabetes mellitus is one of the rapidly growing global health concerns of the twenty-first century ravaging millions of individuals from all across the world. The aim of this study is to evaluate glycemic control status and its associated factors among diabetes patients on follow-up at referral hospitals of Northwest Ethiopia.

MATERIALS AND METHODS

A cross-sectional study was conducted among diabetes patients between February and June 2020. Four hundred twenty-three randomly selected adult patients were enrolled. Using standardized questionnaire, sociodemographic, behavioral and clinical data were collected. Lipid profiles, fasting blood sugar, glycated hemoglobin, and anthropometric indicators were determined. Bivariate and multivariate binary logistic regression analysis was performed.

RESULT

The magnitude of suboptimal glycemic control was 73.5% (95% CI: 69.29%, 77.71%) among diabetic patients. Marital status [AOR (95% CI) 0.45 (0.20, 0.99), p < 0.05], medication non-adherence [poor: AOR (95% CI) 3.55 (1.81, 6.98)], duration with diabetes mellitus [AOR (95% CI) 3.16 (1.89, 5.28), p < 0.05], type of diabetes (type II referent) [AOR (95% CI) 2.53 (1.47,4.37), p < 0.05], and no use of other drugs [AOR (95% CI) 1.76 (1.05,2.96), p < 0.05] were significantly associated with suboptimal glycemic control.

CONCLUSION

A considerable number of patients with diabetes had suboptimal glycemic control. The suboptimal glycemic control has been contributed by marital status, medication non-adherence, duration with diabetes mellitus, type of diabetes and use of other drugs. These highlights the need for tailored management focusing on the identified associated factors to maintain good glycemic control.

Glycemic Control and its Predictors among Adult Diabetic Patients attending Mettu Karl Referral Hospital, Southwest Ethiopia: A Prospective Observational Study

INTRODUCTION

The current estimate is that 463 million people worldwide have diabetes. In 2017, an estimated 5 million (9.9%) deaths worldwide among adults were caused by diabetes. The burden of disease associated with uncontrolled diabetes is substantial in terms of mortality and cardiovascular disease. The aim of this study was to assess glycemic control level and its predictors among adult patients with diabetes.

METHODS

A prospective observational study was conducted among patients with diabetes during follow-up at an ambulatory clinic of Mettu Karl referral hospital from 15 April to 09 August 2019. The consecutive sampling method was used to collect data, following which the data were entered into Epidata manager version 4.4.2 and exported to the SPSS version 24.0 statistical software package for analysis. Logistic regression analysis was performed to identify predictors of poor glycemic control. Variables whose significance level was < 0.05 (p value) were considered to be predictors of poor glycemic control.

RESULTS

A total of 330 diabetic patients were included in the study, among whom 240 (72.7%) had poor glycemic control. The predictors of poor glycemic control in the multivariate logistic regression analysis were overweight [adjusted odds ratio (AOR) 4.07; 95% confidence interval (CI) 1.60, 10.36; p = 0.003], obesity (AOR 4.39; 95% CI 1.59, 12.14; p = 0.004), higher estimated glomerular filtration rate (eGFR) (AOR 2.34; 95% CI 1.23, 4.44; p = 0.010), type 1 diabetes (AOR 3.22; 95% CI 1.58, 6.55; p = 0.001), poor diet adherence (AOR 6.95; 95% CI 3.63, 13.32; p < 0.001) and non-adherence to medications (AOR 5.82; 95% CI 2.77, 12.26; p < 0.001).

CONCLUSION

Almost three-quarters of the study population of diabetic patients had poorly controlled blood sugar. Overweight, obesity, higher eGFR, type 1 diabetics, poor adherence to diet recommendation and non-adherence to medications were independent predictors of poor glycemic control. Educational strategies should focus on improving adherence to the recommended diet and medication(s), achieving weight control and optimizing glycemic control.

How Much Do We Know about the Biopsychosocial Predictors of Glycaemic Control? Age and Clinical Factors Predict Glycaemic Control, but Psychological Factors Do Not

OBJECTIVE

Diabetes mellitus is one of the most common noncommunicable diseases in Malaysia. It is associated with significant complications and a high cost of treatment, especially when glycaemic control is poor. Despite its negative impact on health, data is still lacking on the possible biopsychosocial predictors of poor glycaemic control among the diabetic population. This study is aimed at determining the prevalence of poor glycaemic control as well as its association with biopsychosocial factors such as personality traits, psychiatric factors, and quality of life (QOL) among Malaysian patients with diabetes.

METHODS

A cross-sectional study was conducted at the Universiti Kebangsaan Malaysia Medical Centre (UKMMC) using outpatient population diabetic patients. Demographic data on social and clinical characteristics were collected from participants. Several questionnaires were administered, including the Beck Depression Inventory-II (BDI-II) to measure depressive symptoms, the Generalized Anxiety Disorder-7 (GAD-7) to assess anxiety symptoms, the Big Five Inventory (BFI) to evaluate personality traits, and the WHO Quality of Life-BREF (WHOQOL-BREF) to assess QOL. Multivariate binary logistic regression was performed to determine the predictors of poor glycaemic control.

RESULTS

300 patients with diabetes mellitus were recruited, with the majority (90%) having type 2 diabetes. In this population, the prevalence of poor glycaemic control (HbA_1C ≥ 7.0%) was 69%, with a median HbA_1C of 7.6% (IQR = 2.7). Longer duration of diabetes mellitus and a greater number of days of missed medications predicted poor glycaemic control, while older age and overall self-perception of QOL protected against poor glycaemic control. No psychological factors were associated with poor glycaemic control.

CONCLUSION

This study emphasizes the importance of considering the various factors that contribute to poor glycaemic control, such as duration of diabetes, medication adherence, age, and QOL. These findings should be used by clinicians, particularly when planning a multidisciplinary approach to the management of diabetes.

Glycemic Control Among People Living with Diabetes and Human Immunodeficiency Virus in Ethiopia: Leveraging Clinical Care for the Looming Co-Epidemics

BACKGROUND

Antiretroviral therapy has decreased human immunodeficiency virus related mortality. However, the incidence of diabetes mellitus is increasing among people living with human immunodeficiency virus and adds complexity to the standards of care.

OBJECTIVE

The study was aimed to determine the glycemic control and delivery of clinical care among people living with diabetes and human immunodeficincy virus in Ethiopia.

METHODS

A comparative prospective cohort study was conducted among patients living with diabetes at follow-up clinics of Jimma Medical Center in two study arms. The first arm was people living with diabetes and human immunodeficiency virus. The second arm was human immunodeficiency virus negative patients living with diabetes. The expanded English version of the summary of diabetes self-care activities scale was used to measure self-care behaviors. In order to identify the predictors of glycemic control, multivariable Cox regression analysis was used. Statistical significance at p-value ≤0.05 was considered.

RESULTS

A total of 297 eligible participants were followed for one year, with a mean age of 44.35±12.55 years. Males accounted for 55.9%. After one year of follow-up, 61.9% of diabetes people living with human immunodeficiency virus, and 49% of human immunodeficiency virus-negative patients with diabetes poorly met blood glucose target (p=0.037). Female gender [AHR: 2.72; 95% CI (1.21-5.72)], age >31 years [AHR: 2.48; 95% CI (1.34-11.01)], increased waist circumference [AHR: 3.64; 95% CI (2.57-16.12)], overweight [AHR: 3.63; 95% CI (1.65-22.42)], chronic disease comorbidity [AHR: 2.02; 95% CI (1.44-2.84)], human immunodeficiency virus infection [AHR: 3.47; 95% CI (2.03-23.75)], living longer with diabetes (>5 years) [AHR: 3.67; 95% CI (3.26-4.14)] showed a higher risk of blood sugar control failure and were independent predictors of uncontrolled glycemia. Tuberculosis infection increased the risk of uncontrolled blood sugar among people living with diabetes and human immunodeficency virus[AHR:3.82;95% CI(2.86-5.84].

CONCLUSION

Significant gaps were observed in achieving the recommended glycemic target and involvement of patients on self-care care behavior in the study area. The co-occurrence of tuberculosis, human immunodeficiency virus, and diabetes is triple trouble needing special attention in their management. It is high time to leverage the clinical care of the looming co-epidemics through chronic comprehensive care clinic.

Predictors of poor adherence to antidiabetic therapy in patients with type 2 diabetes: a cross-sectional study insight from Ethiopia

BACKGROUND

Poor adherence to the medical regimen is a major clinical problem in the management of patients with diabetes. This study sought to investigate the level of medication adherence to antidiabetic therapy and to identify possible predictors of poor adherence.

METHODS

A hospital based cross-sectional study was conducted from July 2018 to June 2019 among randomly selected follow-up T2D patients at a hospital diabetes clinic. Data were collected through patient interviews, followed by medical chart review. Adherence to antidiabetic therapy that we assessed patients' responses using validated Brief Medication Questionnaire (BMQ). To identify predictors of poor medication adherence, binary logistic regression analyses were performed using SPSS version 25. Statistical significance was set at p value ≤ 0.05.

RESULTS

Of the total 357 study participants, 25% were non-adherent to their antidiabetic therapy. Predictors statistically associated with poor adherence were; being female gender (AOR = 1.71, 95% CI 1.01-2.76), and presence of at least one diabetic complication (AOR = 2.02, 95% CI 1.02-3.22). Participants with having at least primary level of education were more likely to adhere to anti-diabetes medication (AOR = 0.42, 95% CI 0.18-0.96). The most common self-reported reasons for non-adherence were forgetfulness, unavailability of medication plus the unaffordability of anti-diabetes medications.

CONCLUSIONS

The proportion of participants' adherent to anti-diabetes therapies was suboptimal. Being female, the presence of chronic diabetic complications and having no formal education were the main predictors of poor adherence. Strategies that aimed at improving adherence to antidiabetic medications deemed to be compulsory.

Influence of Health Literacy on Medication Adherence Among Elderly Females With Type 2 Diabetes in Pakistan

Health literacy is how well the patients are able to attain, deal with, and understand basic health information. This is particularly important when it comes to comprehending prescribed medication instructions. To improve the communication strategies for health-care professionals during patient counseling, our study aimed to assess the influence of health literacy and medication adherence in older patients. The objectives of the study were to evaluate associations that occur between the level of health literacy and medication adherence. This study used a convenience sampling method of females (older than 60 years) attending the diabetic clinic in two hospital settings (N = 524). All study participants filled three validated questionnaires: these were the Literacy Assessment for Diabetes, the Diabetes Numeracy Test, and a modified Brief Adherence Rating Scale. To assess the spectrum of health literacy differences, we used χ² analysis and linear regression analysis. Individuals with adequate health literacy were more likely to remember to take their medications compared with those with inadequate health literacy, χ²(4) = 11.6, p = .04. Adequate literacy level study participants were more likely to not change the dose of their medications without medical advice (12.3%) compared with those individuals with inadequate health literacy (2.8%), χ²(4) = 11.13, p = .03. The results in our study suggest that health-care professionals should focus on appropriate communication attuned to the assessment of health literacy levels particularly in older female patients when discussing medication instructions.