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

The Impact of Depression on Adherence to Diabetes Self-Management Behaviors in Breast Cancer Survivors

OBJECTIVE

Breast cancer survivors (BCS) have higher rates of depression which is associated with lower adherence to medications, diet, and physical activity. Managing diabetes (DM) requires adherence to several of these self-management behaviors (SMB), and BCS have an increased risk of DM. We investigated whether depressive symptoms were associated with adherence to DM SMB in a cohort of BCS.

METHODS

BCS with DM were surveyed semiannually for 2 years. Depression was assessed with the Hospital Anxiety and Depression Scale (HADS). Adherence to DM medication, diet, and physical activity was self-reported using the Medication Adherence Report Scale (MARS), Summary of Diabetes Self-Care Activities Assessment (SDSCA), and International Physical Activity Questionnaire (IPAQ), respectively. Using generalized linear equation modeling, the association of depressive symptoms with nonadherence to SMB was assessed, adjusting for age, race, marital status, education level, and beliefs about cancer and DM risk.

RESULTS

Among 244 BCS with DM, those who were nonadherent to medication, diet, and/or physical activity had higher depression scores (p < 0.01). In adjusted analyses, higher depression scores were independently associated with dietary (OR = 1.16, p < 0.001) and physical activity nonadherence (OR = 1.18, p < 0.001) but not with medication nonadherence. Concerns about medications was independently associated with medication nonadherence (OR = 1.17, p = 0.024).

CONCLUSIONS

Higher depression scores are associated with nonadherence to DM SMB in this cohort of BCS. These findings highlight the importance of addressing depressive symptoms in BCS to help improve adherence to DM medications, diet, and physical activity.

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.

Prevalence of and factors associated with suboptimal glycemic control among patients with type 2 diabetes mellitus attending public hospitals in the Greater Male' Region, Maldives: a hospital-based cross-sectional study

BACKGROUND

Suboptimal glycemic control of type 2 diabetes mellitus (T2DM) which is defined as having HbA1c greater than 7% is a major public health problem in several countries, including the Maldives. The study aimed to estimate the prevalence and determine factors associated with suboptimal glycemic control among T2DM patients.

METHODS

A hospital-based cross-sectional was applied to collect data from T2DM patients who attended public hospitals in the Greater Male' Region, Maldives where were one of the highest reports of T2DM and suboptimal glycemic control cases in the country between January to March 2023 by a validated questionnaire and anthropometric measurements. Five (5) ml blood specimens were collected to measure the glycated hemoglobin (HbA1c) level. Univariable and multivariable logistic regressions were employed to determine factors associated with suboptimal glycemic control of T2DM at a significant level of α = 0.05.

RESULTS

A total of 341 participants were recruited for the study: 65.7% were female, 42.5% were aged 40-60 years, and 42.2% were married. The overall prevalence of suboptimal glycemic control was 50.7%. Ten variables were found to be associated with suboptimal glycemic control in multivariable logistic regression. Those aged 40-60 years (AOR = 3.35, 95% CI = 1.78-6.30), being single (AOR = 2.53, 95% CI = 1.21-5.30), preparation of food using more than three tablespoons of cooking oil (AOR = 2.78, 95% CI = 1.46-5.28), preparation of food with more than three tablespoons of sugar (AOR = 2.55, 95% CI = 1.31-4.93), no exercise (AOR = 2.04, 95% CI = 1.15-3.61), DM diagnosed with more than twenty years prior (AOR = 2.59, 95% CI = 1.34-4.99), obese body mass index (BMI) (AOR = 3.82, 95% CI = 1.75-8.32), high total cholesterol (AOR = 2.43, 95% CI = 1.36-4.35), high triglycerides (AOR = 3.43, 95% CI = 1.93-6.11), and high-level stress (AOR = 2.97, 95% CI = 1.48-5.93) were having a greater odds of having suboptimal glycemic control than those who did not have these characteristics.

CONCLUSION

A large proportion of T2DM patients in the Greater Male' Region fail to control their blood glucose. Effective public health interventions should be introduced, especially interventions focused on reducing cooking oil and sugar in daily cooking practices, encouraging regular exercise, and maintaining cholesterol levels, particularly for those diagnosed with diabetes mellitus for more than 20 years prior.

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.

Association of Met420del Variant of Metformin Transporter Gene SLC22A1 with Metformin Treatment Response in Ethiopian Patients with Type 2 Diabetes

Objective

This study aimed to evaluate whether the M420del variants of SLC22A1 (rs72552763) is associated with metformin treatment response in Ethiopian patients with type 2 diabetes mellitus (T2DM).

Patients and Methods

A prospective observational cohort study was conducted on 86 patients with T2DM who had been receiving metformin monotherapy for <1 year. Patients showing ≥0.5% reduction in HbA1c levels from baseline within 3 months and remained low for at least another 3 months were defined as responders while those patients with <0.5% reduction in HbA1c levels and/or those whom started a new class of glucose-lowering drug(s) because of unsatisfactory reduction were defined as non-responders. In addition, good glycemic control was observed when HbA1c ≤7.0%, and the above values were regarded as poor. Genotyping of rs72552763 SNP was performed using TaqMan® Drug Metabolism Enzyme Genotyping Assay and its association with metformin response and glycemic control were assessed by measuring the change in HbA1c and fasting blood glucose levels using Chi-square, logistic regression and Mann-Whitney U-test. Statistical significance was set at p <0.05.

Results

The minor allele frequency of the rs72552763 SNP of SLC22A1 was 9.3%. Metformin response was significantly higher in deletion_GAT (del_G) genotypes as compared to the wild-type GAT_GAT (G_G) genotypes. Furthermore, a significantly lower median treatment HbA1 level was found in del_G genotypes as compared to G_G genotypes. However, the association of rs72552763 with metformin response was not replicated at the allele level. In contrast, the minor del_allele was significantly associated with good glycemic control compared to the G_allele, though not replicated at del_G genotypes level.

Conclusion

This study demonstrated that metformin response was significantly higher in study participants with a heterozygous carrier of M420del variants of SLC22A1 as compared to the wild-type G_G genotypes after 3 months of treatment.

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.

Physical activity can improve diabetes patients' glucose control; A systematic review and meta-analysis

Background

Glycemic control is vital to patient care, and it is still the most important treatment goal for reducing organ damage and other complications associated with diabetes. Physical activity is one of the factors that affects glycemic management. Therefore, the aim of this systematic review and meta-analysis was to find, evaluate, and synthesize the best available information on the link between physical exercise and glycemic control in Ethiopian diabetes patients.

Methods

Pubmed, Science Direct, Google Scholar and African Journals Online were the databases searched. In addition, gray literature were explored. All papers chosen for inclusion in the review underwent a thorough critical appraisal utilizing the Joanna Briggs Institute's standardized critical appraisal instruments (JBI critical appraisal checklist-2017). For statistical analysis and descriptive synthesis, quantitative articles were combined. The Odds ratio and their 95% confidence intervals were generated. Papers that were of excellent quality but lacked the main outcome (physical activity) for meta-analysis were subjected to descriptive synthesis.

Results

The finding of this meta-analysis showed diabetes patients who were physically active had controlled their blood glucose levels by 2.4 times compared to their counter (Odds ratio = 2.40, 95% Confidence Interval = 1.57,3.69). The duration of disease was found to be the most commonly reported predictor for poor glycemic control followed by dietary habits, patients' sex and age.

Conclusion

Physical activity, which is a simple and inexpensive therapy for diabetes patients, can help them control their blood glucose levels. Patients with diabetes who have had it for a long time should be aware of the need of regular physical activity in maintaining blood glucose control.

Poor Self-Care Practices and Being Urban Resident Strongly Predict Chronic Complications Among Patients with Type 2 Diabetes in Eastern Ethiopia: A Hospital-Based Cross-Sectional Study

Background

Diabetes, together with its complications, has a considerable negative influence on people's quality of life and healthcare delivery and raises diabetic mortality. However, there is limited information about the diabetes-associated chronic complications in the study setting. Therefore, this study aimed to determine the burden and factors related to the chronic complications among patients with type 2 diabetes (T2D) in Eastern Ethiopia.

Methods

A hospital-based cross-sectional study was conducted among 879 patients with T2D at two public hospitals in Harar. The data were collected through interviews using a structured questionnaire. Data related to the diagnosis of chronic complications and biochemical tests were extracted from medical records. The outcome variable was the number of chronic complications that happened to the patients. A generalized Poisson regression model with robust variance estimation was used to investigate the association of independent variables with chronic complications. An adjusted prevalence ratio with a 95% CI was reported to show an association using a p-value ≤0.05.

Results

One or more chronic complications were presented in 43% of T2D (95% CI: 39.65, 46.19). Macrovascular and microvascular complications were found in 27.6% and 23.5% of patients, respectively. Urban residence (APR = 2.64; 95% CI: 1.54, 4.54), low wealth status (APR = 1.80; 95% CI: 1.17, 2.76), diabetes duration ≥5 years (APR = 1.46; 95% CI: 1.05, 2.01), hypertriglyceridemia (APR = 1.48; 95% CI: 1.07, 2.09) and poor self-care practices (APR = 1.62; 95% CI: 1.18, 2.23) were factors significantly associated with the chronic complications.

Conclusion

The burden of chronic complications was high, with nearly half of T2D patients experiencing one or more chronic complications. Almost one in ten patients suffered from multiple chronic complications. The complications were mainly influenced by being urban resident, low wealth status, and poor self-care practices. Therefore, health care providers need to educate patients and promote self-care practices and healthy lifestyles to achieve treatment goals and lower the risk of chronic complications.

Glycemic Control for Type 2 Diabetes Mellitus Patients: A Systematic Review

Diabetes mellitus is a chronic metabolic disorder resulting in hyperglycemia and microvascular and macrovascular complications in individuals globally. Type 2 diabetes mellitus (T2DM) is highly prevalent and accounts for 90% of patients. Maintaining blood glucose concentration is essential to avoid severe complications.

Glycemic control is the optimal serum glucose concentration in diabetic patients. It is necessary to identify factors affecting the glycemic control of patients to prevent control and complications. We conducted this systematic review to assess the factors affecting glycemic control among type 2 diabetes mellitus patients.

Published literature between the years 2020 to 2022 was retrieved from PubMed, Science Direct, and Google Scholar using different combinations of keywords: T2DM, Glycemic control, Poor, Good, Adequate, Inadequate, Factors, Association, and Determinants. All original articles written in the English language with full-text available and the value of glycemic control defined were included. A total of 1866 studies were retrieved. After the title, abstract, screening, and full-text screening, 12 studies were eligible.

The prevalence of poor glycemic control was high, and it ranged between 45.2% and 93% among the studies. The factors associated with glycemic control were stratified into four categories: personal or body-related, clinical, medication-related, and behavioral factors. There was a high prevalence of poor glycemic control in all included studies. The glycemic control was associated with various factors; some were related to the patient or medical conditions while others were related to the behavior of the patients or the medication administrated.