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.

Factors associated with poor glycemic control among adult patients with type 2 diabetes mellitus in Gamo and Gofa zone public hospitals, Southern Ethiopia: A case-control study

BACKGROUND

Diabetes mellitus is a serious global public health problem that affects the whole life of people in terms of their biological, psychological, and social effects. Complications and death from diabetes occur from poorly controlled blood glucose levels. 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 factors associated with poor glycemic control among type2 diabetes patients in public hospitals of Gamo and Gofa zone southern, Ethiopia, 2021.

METHODS

An institution-based unmatched case-control study was employed among 312 randomly selected participants using a pre-tested, interviewer-administered, and structured questionnaire. Bivariate and multivariable logistic regression analysis was conducted to identify factors associated with poor glycemic control using IBM SPSS version 25. The strength of association was assessed by using an Adjusted odds ratio (AOR) with a 95% confidence interval (CI).

RESULT

Factors associated with poor glycemic control based on multivariable analysis were, having comorbidity (AOR = 2.35, 95% CI (1.39-3.95)), adhering to dietary recommendations (AOR = 0.31, 95% CI (089-0.51)), poor social support (AOR = 3.31, 95% CI (1.59-6.85)), physical exercise (AOR = 1.86 95% CI (1.11-3.12)), and having poly-pharmacy (AOR = 2.83, 95% CI (1.39-5.74)).

CONCLUSION AND RECOMMENDATION

This study indicated a significant association of comorbidity, physical exercise, poly-pharmacy, low social support, and adherence to dietary recommendations with poor glycemic control. We suggest that the health care providers and concerned bodies encourage patients to have regular check-ups and work on providing necessary social support.

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.

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.

Glycemic control and its associated factors in type 2 diabetes patients at Felege Hiwot and Debre Markos Referral Hospitals

Poor glycemic control is a main public health problem among type 2 diabetes mellitus (T2DM) patients and a significant cause of the development of diabetic complications. This study aimed to assess the glycemic control status and its associated factors among type 2 diabetes patients in Felege-Hiwot and Debre Markos Referral Hospitals. A retrospective cohort study was conducted at Felege-Hiwot and Debre Markos Referral Hospitals from December 2014 to December 2015. We have reviewed the chart of these patients until January 2020. Type 2 diabetic patients on follow-up at Felege-Hiwot and Debre Markos Referral Hospitals who fulfilled the inclusion criteria of the study were included. The primary outcome was the level of blood glucose during the study period. Good glycemic control was defined as patients whose average fasting blood glucose measurement for three consecutive visits was between 70 and 130 mg/dL. A generalized linear mixed autoregressive order one model was used to identify the determinants of glycemic control. A total of 191 patients with 1740 observations were included in the study. The overall prevalence of good glycemic control was 58.4% (95% CI: 57.159.7%). The factors associated with good glycemic control at 95% confidence level adjusted odds ratio were being residing in rural (CI: 0.454, 0.614), negative proteinuria (CI: 1.211, 1.546), diastolic blood pressure < 90 (CI: 1.101, 1.522), systolic blood pressure < 140 (CI: 1.352, 1.895), serum creatinine (CI: 0.415, 0.660), duration per visit (CI: 0.913, 0.987), duration since diagnosis (CI: 0.985, 0.998), weight ≥ 78 kg (CI: 0.603, 0.881). Age 38–50, 51–59 and 60–66 years (CI: 1.267, 1.776), (CI: 1.057, 1.476) and (CI: 1.004, 1.403), respectively. The overall prevalence of poor glycemic control was high at Debre Markos and Felege Hiwot Referral Hospital. Living in a rural area, older age (≥ 67 years), positive proteinuria, higher weight (≥ 78 kg), higher serum creatinine levels, higher duration per visit, higher time duration of T2DM since diagnosis, and developing hypertension (SBP ≥ 140, DBP ≥ 90) were the predictors of lower good glycemic control achievements of T2DM patients. In response to this finding, an aggressive intervention that targets improving glycemic control is required.

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.

High atherogenic risk concomitant with elevated HbA1c among persons with type 2 diabetes mellitus in North Ethiopia

BACKGROUND

Type 2 diabetes mellitus (T2DM) is a chronic disease associated with worse clinical presentation. However, the current investigation practices in Ethiopia have limitations to demonstrate the scope of the clinical burden. Hence, this study was aimed at assessing the glycemic status and coronary heart disease (CHD) risk of persons with T2DM using HbA1c and atherogenic index of plasma (AIP).

METHOD

This institution-based cross-sectional study was conducted among 421 adults with T2DM from September to November 2019. Demographic, socioeconomic, and lifestyle data were collected through a face-to-face interview. Clinical information was retrieved from medical records whereas anthropometric and biochemical measurements were performed using the WHO protocols. Glycemic status was determined using HbA1c and CHD risk assessed using an atherogenic index of plasma (AIP). Gaussian variables were expressed using mean and standard deviation (SD), Log-normal variables using geometric mean and 95% CI and non- Gaussian variables using median and interquartile ranges. Categorical variables were summarized using absolute frequencies and percentages. Multivariable logistic regression was used to identify factors associated with glycemic control with a statistical significance set at 5%.

RESULT

A total of 195 male and 226 female subjects were involved in this study. The results demonstrated that 77% (324) had HbA1c value ≥7% and 87.2% (367) had high atherogenic risk for CHD. Besides, 57% and 67.9% of persons with T2DM had metabolic syndrome according to International Diabetes Federation (IDF) and the National Cholesterol Education Program-Adult treatment panel III (NCEP-ATP III) criteria, respectively. About 36.8% had one or more comorbidities. Having healthy eating behavior [AOR 1.95; CI 1.11-3.43] and taking metformin [AOR 4.88; CI 1.91-12.44] were associated with better glycemic outcomes.

CONCLUSION

High AIP level concomitant with poor glycemic control indicates increased risk for coronary heart disease among persons with T2DM in Northern Ethiopia.

A systematic review and meta-analysis of non-adherence to anti-diabetic medication: Evidence from low- and middle-income countries

BACKGROUND

Non-adherence to anti-diabetic medication is an important cause of uncontrolled blood glucose that leads to complications of diabetes. However, there is a lack of evidence on the burden of and factors associated with non-adherence to anti-diabetic medication among individuals living with diabetes in low-and middle-income countries (LMICs).

OBJECTIVES

This systematic literature review and meta-analytic synthesis aims to estimate non-adherence to anti-diabetic medication reported among individuals in LMICs and explores factors affecting non-adherence.

METHODS

We systematically searched MEDLINE and Embase to identify studies investigating non-adherence to anti-diabetic medications published from January 2000 to May 2020. Two authors carried out study selection, screening, and data extraction independently. Cross-sectional studies that had been conducted among individuals with diabetes in LMICs were eligible for the selection process. Critical appraisal of the included studies was carried out using the Newcastle Ottawa Scale. Meta-analysis was carried out using Stata 14.2. Random effects model was used to compute the pooled proportion at a 95% confidence interval (CI).

RESULTS

Forty-three studies met the inclusion criteria, of which 13 studies were used in meta-analysis. The pooled proportion of non-adherence to anti-diabetic medications using the eight-item Morisky Medication Adherence Scale (MMAS-8) was 43.4% (95% CI: 17.5-69.4; P < 0.001) and 29.1% (95% CI: 19.8-38.4; P < 0.001) when using the cut-off at 80 or 90%. The pooled proportion of non-adherence was 29.5% (95% CI: 25.5-33.5; P = .098) when using the four-item Morisky Medication Adherence Scale (MMAS-4). Using the World Health Organization (WHO) five dimensions of medication adherence framework, the factors contributing to non-adherence were varied, including disease factors, therapy-related factors, healthcare system factor, patient-centred factors, and socio-economic factors.

CONCLUSIONS

Non-adherence to anti-diabetic medication remains an ongoing challenge in LMICs and several factors operating at different levels were cited as reasons. Comprehensive intervention strategies are urgently needed to address these factors in effectively tackling medication non-adherence in LMICs.

Association Between the Level of Reported Good Medication Adherence and the Geographic Location of a Patient's Residence and Presence of a Glucometer Among Adult Patients with Diabetes in Ethiopia: A Systematic and Meta-Analysis

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Seven thousand seven hundred fifty-six participants were included for the final analysis.

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Reported good medication adherence among adult diabetic patients in Ethiopia was 68.59%.

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Reported good medication adherence among adult diabetic patients in regions was 67.81%.

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Reported good medication adherence among adult diabetic patients in Addis Ababa was 70.37%.

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Presence of glucometer at home has positive association with reported good medication adherence among adult diabetic patients.

Background

Diabetes mellitus (DM) is a major public health problem worldwide that was estimated to have affected the lives of 425 million people globally in 2017. The prevalence and mortality rates of DM have increased rapidly in low- and middle-income countries with an estimated 2.6 million cases of DM occurring in Ethiopia alone in 2015.

Objective

Considering that Ethiopia is undergoing an epidemiological transition, it is increasingly important to understand the significant influence DM has on Ethiopians annually. A systematic review and meta-analysis of the existing studies were conducted to better understand the factors that are associated with DM medication adherence across Ethiopia and to elucidate areas for further studies.

Methods

Studies were retrieved through search engines in Cumulative Index to Nursing and Allied Health Literature, Embase, Medline, PubMed, Google Scholar, Web of Science, Science Direct, and Scopus. The Newcastle–Ottawa Scale for cross-sectional studies was used to assess the critical appraisal of the included studies. Random effects model was used to estimate the association between the level of medication adherence and the geographic location of a patient's residence and presence of a glucometer at 95% CI with its respective odds ratio. Meta-regression was also used to identify the potential source of heterogeneity. Beggs and Egger tests were performed to determine publication bias. Subgroup analyses, based on the study area, were also performed.

Results

A total of 1046 articles were identified through searching, of which 19 articles representing 7756 participants were included for the final analysis stage. Reported good medication adherence among patients with diabetes in Ethiopia was 68.59% (95% CI, 62.00%–75.18%). Subgroup analysis was performed, and the pooled estimate of reported good medication adherence among these patients in regions outside Addis Ababa was 67.81% (95% CI, 59.96%–75.65%), whereas in Addis Ababa it was 70.37% (95% CI, 57.51%–83.23%). Patients who used a glucometer at home had an odds ratio of 2.12 (95% CI, 1.42–3.16) and thus reported good adherence. We found no statistically significant association between the geographic location of a patient's residence and a good level of reported medication adherence (odds ratio, 1.81; 95% CI, 0.78–4.21).

Conclusions

Most adult patients with diabetes in these studies had a good level of reported DM medication adherence. Having a glucometer was significantly associated with reported increased medication adherence. Our findings suggest the need for interventions to improve diabetes medication adherence.