Glycemic control and diabetes complications among adult type 2 diabetic patients at public hospitals in Hadiya zone, Southern Ethiopia

Abraham Lomboro Dimore; Zerihun Kura Edosa; Asmelash Abera Mitiku

doi:10.1371/journal.pone.0282962

Abstract

Background

Diabetes is one of the biggest worldwide health emergencies of the 21^st century. A major goal in the management of diabetes is to prevent diabetic complications that occur as a result of poor glycemic control. Identification of factors contributing to poor glycemic control is key to institute suitable interventions for glycemic control and prevention of chronic complications.

Methods

A hospital-based cross-sectional study was conducted among 305 adult type 2 diabetic patients at public hospitals in Hadiya zone from March 1–30, 2019. The study participants were selected by systematic sampling technique. Data were collected using a pretested structured questionnaire and patient chart review; anthropometric and blood pressure measurements were taken. Multivariable logistic regression analysis was used to identify factors associated with poor glycemic control. Adjusted odds ratios (AOR) with respective 95% Confidence Interval (CI) and p < 0.05 were used to set statistically significant variables.

Results

Out of 305 diabetic patients, 222 (72.8%) were found to have poor glycemic control. Longer duration of diabetes (5–10 years) [AOR = 2.24, 95% CI: 1.17–4.27], lack of regular follow-up [AOR = 2.89, 95% CI: 1.08–7.71], low treatment adherence [AOR = 4.12, 95% CI: 1.20–8.70], use of other alternative treatments [AOR = 3.58, 95% CI: 1.24–10.36], unsatisfactory patient physician relationship [AOR = 2.27, 95% CI: 1.27–4.04], and insufficient physical activity [AOR = 4.14, 95% CI: 2.07–8.28] were found to be independent predictors of poor glycemic control. Diabetes Mellitus (DM) complications were slightly higher among participants with poor glycemic control (39.2%), duration of DM 10 and above years (41.9%), low medication adherence (48.5%), taking oral anti-diabetics (54.3%), and DM patients having unsatisfactory patient provider relationship (72.4%).

Conclusion

A significant proportion of diabetic patients had poor glycemic control and DM complications. Therefore, appropriate interventions are required to maintain optimal glycemic control and prevent the development of life-threatening complications among DM patients.

Citation: Dimore AL, Edosa ZK, Mitiku AA (2023) Glycemic control and diabetes complications among adult type 2 diabetic patients at public hospitals in Hadiya zone, Southern Ethiopia. PLoS ONE 18(3): e0282962. https://doi.org/10.1371/journal.pone.0282962

Editor: Suman S. Thakur, CCMB: Centre for Cellular and Molecular Biology CSIR, INDIA

Received: November 29, 2021; Accepted: February 27, 2023; Published: March 23, 2023

Copyright: © 2023 Dimore et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All the relevant data are within the paper and its Supporting Information files.

Funding: The author(s) received no specific funding for this work.

Competing interests: The authors have declared that no competing interests exist.

Introduction

Diabetes Mellitus (DM) refers to a group of common metabolic disorders that has a main characteristic feature of hyperglycemia [1]. Globally, an estimated 463 million people (9.3% of adults, 20–79 years) were living with diabetes in 2019. Its age-standardized prevalence increased by 62% within 10 years; from 285 million in 2009 to 463 million in 2019. The number of people living with diabetes was predicted to rise to 10.2% (578 million) by 2030 and 10.9% (700 million) by 2045 [2]. In 2019, an estimated more than four million adults died of diabetes and its complications (11.3% of all-cause mortality) [3].

The African region, where diabetes was once rare, has witnessed a surge in the condition. Its prevalence in this region among 20–79 years adults is 4.7%. According to global projections for 2030 and 2045, DM prevalence in the region is predicted to rise to 5.1% and 5.2%, respectively [2]. In 2019, there were around 366,227 deaths attributed to diabetes, with 73.1% of these deaths occurring in people under the age of 60 years, which was higher in proportion to any other region in the world [3].

In Ethiopia, diabetes prevalence is increasing among the adult population. According to the report from systematic review and meta-analysis the prevalence of DM in Ethiopia was 6.5% [4]. It is becoming a growing public health problem along with other non-communicable diseases in Ethiopia. Furthermore, its prevalence is also reported increasingly across different localities of the country, which is 0.3% for the lowest and 7.0% for the highest prevalence [5].

For successful control of risk resulting from long-term diabetic complications, optimal glycemic control is paramount. Deprived and insufficient glycemic control among patients with type 2 diabetes establishes a main public health problem and the foremost risk for the development of diabetic complications. Uncontrolled diabetes mellitus leads to micro-vascular and macro-vascular complications [1]. Furthermore, these complications due to poorly controlled diabetes are major causes of disability, premature death, and reduced quality of life [6].

Evidence in Ethiopia has reported that with increasing prevalence and related complications, diabetes is becoming a pressing public health problem [5]. Despite this alarming growth in the prevalence of diabetes, little has been studied regarding glycemic control status, related factors and DM complications. There is a gap and little information is available on these conditions in Ethiopia, particularly in this study area. Therefore, this study aimed to assess glycemic control and DM complications among adult type 2 diabetic patients at public hospitals in Hadiya zone, Southern Ethiopia.

Materials and methods

Study design, area, and study period

A facility-based cross-sectional study was conducted at public hospitals in Hadiya zone from March 1, 2019 to March 30, 2019. Hadiya zone is one of the administrative zones in Southern Nations, Nationalities, and Peoples Regional State (SNNPR). The Zone has four public hospitals (one teaching hospital and three primary hospitals). From these public hospitals, two (Nigist Ellen Mohammed Memorial and Shone primary Hospitals) of them provide chronic illness care for diabetic patients and there are 1,241 diabetic patients (56 type 1 and 1,185 type 2 DM). The hospitals do not have the glycated hemoglobin (HbA1c) test, but the fasting blood glucose of patients was measured based on their follow-up appointment.

Population

All type 2 diabetic patients aged ≥ 18 years old on follow-up at Nigist Ellen Mohammed Memorial and Shone primary hospitals were a source population, and type 2 diabetic patients aged ≥ 18 years old who present during the study period and fulfilled the eligibility criteria were study population. Type 2 diabetic patients on ant-diabetic(s) treatment for at least six months and patients who had at least three consecutive blood glucose measurements in three months were included in this study. Patients with critical illness who were unable to communicate at the time of data collection, patients with hearing problems and previously diagnosed psychiatric illness and pregnant women with diabetes were excluded from the study.

Sample size and sampling technique

The required sample was calculated using a single population proportion estimation formula considering the following assumptions: 59.2% prevalence of poor glycemic control from the study done in Shanan Gibe Hospital, Southwest Ethiopia [7], 95% confidence level (CI), 5% margin of error and 10% non-response rate. Since the source population was less than 10,000, considering the correction formula, the total calculated sample yielded 311.

A systematic random sampling technique was applied to recruit study participants. The diabetic clinic provides services three days per week and on average 92 type 2 diabetic patients are served per day at Nigist Ellen Mohammed Memorial Hospital. In Shone primary hospital, diabetic patients had two days per month for follow-up and on average 40 patients were served per day. The study participants were allocated for both hospitals by proportional to population size allocation. By dividing the total type 2 DM patients eligible (1,185) by the sample size required (311), which yields a sampling interval of four. Sample recruitment was performed concurrently in both hospitals. The first participant was selected by lottery method. Thus, every fourth patient coming to the clinic for a follow-up service was interviewed until the total sample size reached.

Data collection procedure

Data were collected by using pretested structured questionnaires to capture information on socio-demographic and economic characteristics; clinical characteristics; knowledge about diabetes, and attitudes toward DM care; and adherence to diabetic self-care activities. A checklist was used to abstract data from the medical records. Sphygmomanometer, weight scale, and stadiometer were used to measure blood pressure, weight, and height, respectively.

Measurements and operational definition

Fasting blood glucose readings of the last three diabetic clinic visits were obtained from patients’ medical records and computed mean fasting glucose levels. Poor glycemic control was operationally defined if the mean fasting glucose(FBG) level was above 130mg/dL [8].

Adherence to antidiabetic medications was measured by using Morisky Medication Adherence Scale (MMAS 8-item) [9]. The scale contains questions asking the patient to respond "Yes" or "No" to a set of eight questions. A positive response indicated a problem with medication adherence. Therefore, higher scores indicate that a patient has the least adherence to medications. For all questions, responses were coded 1 if patients responded "Yes" otherwise, 0 if not, except one question (Did you take all your medicines yesterday?) that was coded in reverse. The total score was computed and adherence was categorized as high, medium, and low if the participants score was 0, 1–2, and 3–8, respectively.

Patient-provider relationship was measured by using Patient Doctor Relationship Questionnaire (PDRQ_9) consisting of nine questions with a five-point Likert-type scale, where 1 = very inappropriate and 5 = very appropriate [10]. The total score was computed and participants who scored mean and above were considered to have a satisfactory patient-provider relationship.

Knowledge of patients about diabetes was assessed by using eight knowledge questions. Percentage out of total score was computed and participants who answered six (75%) questions out of total knowledge questions correctly were categorized as having good knowledge about diabetes. Attitude of patients towards diabetic care was assessed by using seven questions on a five-point Likert- type scale, where 1 = strongly disagree and 5 = strongly agree. Three items have been negatively worded, which requires reverse coding. Its internal consistency was checked by using reliability statistics with Cronbach’s α = 0.81 during the pretest. The total score was computed and patients were considered as having a positive attitude towards diabetic care if s/he scored mean and above for attitude questions.

Blood pressure was measured after the patient sat and rested for a few minutes with the arm held at a position that was around the heart. Blood pressure was measured twice and recorded from a mean of two measurements as per American Diabetes Association (ADA) recommendations [8]. Study participants whose systolic BP ≥ 140 mmHg and/ or diastolic BP ≥ 90 mmHg or current use of antihypertensive medication irrespective of the current BP were considered as hypertensive.

Anthropometric measurements were measured using standardized techniques and calibrated equipment. The weight of the participants was measured to the nearest 0.1 kg. The scale was placed on a hard surface and the participants were measured by wearing light clothing and bare feet. Height of the participants was measured to the nearest 0.5 cm using a stadiometer. Then, Body Mass Index (BMI) of the participants was calculated as weight in kg divided by height in meters squared and subjects were considered as normal (BMI = 18.5–24.9 kg/m²), overweight (BMI = 25–29 kg/m²) and obese (BMI ≥ 30 kg/m²) [8].

Diabetic self- care activities were assessed by using Summary of Diabetic Self-care Activity measure (SDSCA), which contains 11 items on diet, exercise, self- monitoring of blood glucose, foot care, and cigarette smoking [11]. Exercise was measured based on response to items five and six, then participants who participated in at least 30 minutes of physical activity for 3 or more days or participated in specific exercise session during the last seven days were categorized as having adequate adherence to exercise.

The study participants who used other non-medical treatment options like traditional or herbal medicines and religious healing practices for the treatment of diabetes were considered as having used other alternative treatments. A diabetic patient who visited the diabetic clinic based on appointment regularly within the previous six months was considered to having regular follow-up at the diabetic clinic.

Data management and quality assurance

The questionnaire and checklist were translated from English language to Amharic and Hadiyissa (local language) and translated back to English language to check its consistency. One-day training was given for data collectors and supervisors on the objectives, process of data collection, and how to take anthropometric measurements. Pretest was done on 5% of the sample size in order to check the clarity and internal consistency of the questionnaire and checklist prior to the actual data collection.

The equipment for measuring weight, height, and blood pressure were calibrated to the standard before measuring each participant. Completeness, accuracy, clarity, and consistency of data were checked daily after data collection time by supervisors. The overall activities were monitored by the principal investigators. Finally, the collected data were entered into a computer using epidata3.1 version software.

Statistical analysis

The analysis was done in Statistical Package for the Social Science (SPSS) 20 version software. Descriptive statistics including mean (standard deviation), median (inter-quartile range) and range values for continuous variables; and percentage and frequency tables for categorical variables were employed. Normality assumption was checked for continuous variables.

Bivariate analysis was employed to determine the presence of an association between poor glycemic control and each independent variable using binary logistic regression. Variables that were found significant at p-value less than 0.25 in bivariate analysis were selected as candidate variables for multivariable analysis.

Multivariable analysis was carried out to identify independent predictors of poor glycemic control and to control for confounders. Backward stepwise logistic regression was used to determine independent predictors with P-value less than 0.05 with their respective AOR and 95% CI. The model fitness was tested by using Hosmer and Lemeshow goodness of fit test and was declared fit.

Ethical considerations

The study was approved by Institutional Review Board (IRB) of Institute of Health Sciences at Jimma University; Southwest Ethiopia. Permission to conduct the study was obtained from both hospital administrative offices. We have informed the participants about the objectives of the study, the procedures, and their voluntary participation in the study before conducting the interviews. Then, we obtained informed verbal consent from each participant and it was documented on each participant questionnaire. Data were collected anonymously to ensure confidentiality. Moreover, individual counseling on self-care practices was given for participants with poor glycemic control to maximize the benefits of the study.

Results

Socio-demographic characteristics of the respondents

A total of three hundred and five type two diabetes patients participated in this study with a response rate of 98%. Out of the total participants, 182 (59.7%) were males and the median (IQR) age of the respondents was 44 (19) years, ranging from 19 to 78 years. Nearly half (47.5%) of them were within the age category of 40–60 years. Three fifths (60%) of the respondents were following Protestant religion and four out of five (83.9%) respondents were married. Nearly one third 96 (31.5%) of the respondents attained college and above; 105 (34.4%) were government employees and 212 (69.5%) were urban residents (Table 1).

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Table 1. Socio-demographic and economic characteristics of the study participants attending diabetic clinic at public hospitals in Hadiya zone, Southern Ethiopia, 2019.

https://doi.org/10.1371/journal.pone.0282962.t001

Glycemic control status

Fasting blood glucose readings of the last three diabetic clinic visits were obtained from patients’ medical records. Mean fasting blood glucose (FBG) measurements of the last three months were used to determine glycemic control. The mean (SD) FBG level of the participants was 167.49 (58.183) mg/dL. The minimum and maximum FBG measurements were 90 mg/dL and 478 mg/dL, respectively. The prevalence of poor glycemic control was 72.8% (95% CI: 67.8% -78.1%). The prevalence of poor glycemic control was 72.8% (95% CI: 67.8% -78.1%). Poor glycemic control was higher among government employees (77 [73.3%]), age category 40–60 years (106 [73.1%]), married (186 [72.7%]), male (127 [69.8%]), urban dwellers (146 [68.9%]), and those who attained college and above educational level (65 [67.7%]) (S1 Table).

Diabetes complications

Diabetes-related complications were found in 105 (34.4%) of the study participants. The common DM complication among the study participants were retinopathy (26.7%), foot ulcer (17.1%), nephropathy (14.3%), and neuropathy (10.5%) (S2 Table). The prevalence of DM complications was predominant among participants with duration of 10 and above years (44 [41.9%]), low medication adherence (51 [48.5%]), taking oral anti-diabetics (57 [54.3%]), and DM patients having unsatisfactory patient provider relationship (76 [72.4%]) (Table 2). Likewise, prevalence of DM complications was higher among patients with poor glycemic control 87 (39.2%) than those with good glycemic control.

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Table 2. Clinical and anthropometric characteristics of the study participants attending diabetic clinic at public hospitals in Hadiya zone, Southern Ethiopia, 2019.

https://doi.org/10.1371/journal.pone.0282962.t002

Clinical characteristics of T2 DM patients

The median (IQR) diabetes duration of the participants was 5 (5) years and 133 (43.6%) of the participants had duration of less than five years. Out of total participants, 87 (28.5%) of them had other chronic diseases and 105 (34.4%) of the respondents had diabetes-related complications that were previously diagnosed. Diabetic retinopathy was the most common DM complication, accounting for 73.3% (S2 Table).

Of the total respondents, 50 (16.4%) of them use other alternative treatments for diabetes, of which 44 (88%) use traditional medicine and six (12%) use religious healing practices (S2 Table). Three-fifths (61.3%) of the participants had an unsatisfactory patient-provider relationship and 46 (15.1%) of them did not have regular follow-up at the diabetic clinic within the previous six months. Regarding medication adherence, 105 (34.4%) of the respondents had low adherence (Table 2).

The mean (SD) BMI of the respondents was 24.18 (2.76) Kg/m² and 36.4% of the respondents had overweight. The mean (SD) systolic and diastolic BP was 131.92 (16.42) and 84.72 (7.76) mmHg, respectively. Out of total participants, about 96 (31.5%) of them were hypertensive (Table 2).

Knowledge and attitude towards diabetic care

Of the total participants, 139 (45.6%) had poor knowledge about diabetes and the rest had good knowledge. The mean score for attitude is 28.21 (±3.079) with a minimum score of 17 and a maximum score of 35. Nearly half (48.9%) of the respondents had a negative attitude towards diabetic care.

Factors associated with glycemic control

Bivariate analysis was done to see the association between the independent variables and poor glycemic control. According to bivariate analysis; sex, educational status, marital status, residence, income, duration of diabetes, comorbidity, regular follow-up, use of other alternative treatments, patient-provider relationship, medication adherence, knowledge, attitude, blood pressure, body mass index, and physical activity showed association with poor glycemic control at P-value less than 0.25 (S3 and S4 Tables). These variables were entered into multivariable analysis to determine independent predictors of poor glycemic control.

In multiple logistic regression, a statistically significant difference was found in poor glycemic control due to duration of diabetes, follow-up to DM clinic, medication adherence, using other alternative treatments, unsatisfactory patient-provider relations and insufficient physical activity (Table 3).

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Table 3. Multivariable analysis of factors associated with poor glycemic control among T2 DM adult patients at Public hospital in Hadiya Zone, Southern Ethiopia, 2019.

https://doi.org/10.1371/journal.pone.0282962.t003

Discussion

It is an established fact that diabetes can cause complications in those patients whose blood glucose level is not controlled [1]. The main goal of diabetes management is to ensure optimal glycemic control to delay and prevent complications. This study assessed the prevalence of poor glycemic control and its associated factors among type two diabetic patients.

The findings of this study showed that nearly three-fourths (72.8%) of diabetic patients in the study area had poor glycemic control. This finding was comparable with earlier studies done in Saudi Arabia (74.9%) [12], Tanzania (69.7%) [13], Dessei, Northeast Ethiopia (70.8%) [14], and Jimma, Southwest Ethiopia (70.9%) [15]. However, it is ahigher prevalence than that of studies which reported 64.9% in Nekemte referral Hospital and 59.2% in Shanan Gibe Hospital, Southwest Ethiopia [7, 16]. The possible reason for this high prevalence of poor glycemic control could be the clinical characteristics of the patients, low medication adherence, and insufficient physical activity of the patients in the current study. This finding was lower than a study done in Tikur Anbesa specialized Hospital (TASH), Ethiopia, which reported 80% [17] of the study participants had poor glycemic control. The possible explanation for this difference could be that patients seeking advanced management were referred to TASH and patients from the whole region of the country were referred to TASH [17]. The results of the current study highlight the need to work more on the optimal management of diabetes, since maintaining the recommended glycemic level is the main therapeutic goal for all patients with diabetes.

The current study showed that longer duration of diabetes is significantly associated with poor glycemic control. This finding is consistent with other similar studies [12, 14, 17–19]. However, this finding is slightly lower in strength of association than the finding from a study done in Shanan Gibe Hospital [7]. The possible reason for this difference could be the majority (43.6%) of the patients in the current study had short duration (less than five years) of diabetes, while in that one 49.4% of the participants had long duration (greater than 10 years) of diabetes. The possible explanation for this finding could be due to progressive impairment of insulin secretion over time because of the failure of β-cells and increased insulin resistance to control blood sugar [20]. Moreover, it might be due to difficulty for the patients to continue monitoring of blood glucose level and adjust with the treatment, exercise and diet [21, 22]. Therefore, measures should be put in place for education for diabetes patients, emphasizing more on self-care activities, especially for patients with long duration of diabetes.

In the current study, a lack of regular follow-up was significantly associated with poor glycemic control. This finding is in agreement with previous studies done in Brazil and Southwest Ethiopia [7, 23]. The possible reason for this finding could be that patients who are not regularly following the diabetic clinic might be noncompliant to diabetic self-care activities and treatment [24, 25]. In addition, those patients who are not regularly following the diabetic clinic might not know their blood sugar level and they might not get counseling about their disease condition. This finding implies that health care providers should give attention to encourage the patients to visit the diabetic clinic regularly.

In this study, poor glycemic control appeared to be greater among patients who had low medication adherence compared with high adherence. This finding is comparable with other studies conducted in Jimma and Gondar hospitals [15, 26]. However, the current finding is higher in strength of association than the finding from a study done in Tripoli, Libya [27]. The reason for this difference might be due to the different measurement scores in these two studies. The possible explanation for this finding is that low adherence to treatment is one of the barriers that prevents many diabetic patients from achieving optimal glycemic levels [28]. Furthermore, it might be due to lack of patients’ knowledge about the importance of treatment adherence, which results in better glycemic control. The finding implies that health facilities should consider developing educational programs that emphasize life-style modification with the importance of adherence to treatment would be of great benefit for optimal glycemic control. Moreover, health care providers should discuss barriers to treatment adherence when counseling patients and solutions should be tailored toward individual needs.

In the present study, use of other alternative treatments (traditional medicine and religious healing practices) is significantly associated with poor glycemic control. Patients who used other alternative treatments were more likely to have poor glycemic control. This finding is supported by a systematic review of literature in Sub-Sahara African countries in which the use of herbal medicines and traditional healers was frequently mentioned, although it is not part of the ADA self-management guidelines [29]. A study in Northern Ethiopia also revealed that the majority (62%) of diabetes patients were herbal medicine users and most (87.1%) of them did not consult their physicians about their herbal medicine use [30]. This finding could be due to the fact that patients who used other alternative treatments might be low medication adherent and this might be leading to poor glycemic control [28]. Thus, health care providers should consult patients regarding use of other alternative treatments and encourage them to adhere to prescribed medication.

Having an unsatisfactory patient-provider relationship was found to be an independent predictor of poor glycemic control among type 2 diabetic patients. The possible reason could be those patients who have a satisfactory patient-physician relationship might be well encouraged to act in accordance with self-care activities. The finding implies that health care providers should pay attention to developing effective patient-provider relation and communication skills when counseling diabetic patients.

The current study also revealed that patients with insufficient physical activity had poor glycemic control, which is consistent with prior studies done in Tripoli, Libya, and Jimma, Southwest Ethiopia [27, 31]. Nevertheless, it is lower than the finding from the study done in Saudi Arabia [12]. The variation could be due to that the previous study measured physical activity at least 30 minutes for three days per week, while the current study measured physical activity by mean score for physical exercise done in the last seven days using the SDSCA tool. The possible explanation for this finding might be due to having inadequate knowledge about the benefits of regular physical exercise and a fear of hypoglycemia. This implies that encouraging diabetic patients to do physical exercise is a crucial part of diabetes education for optimal glycemic control. Furthermore, physical exercise has not only been reported to raise glycemic control, but also to improve a patients insulin sensitivity and to repair some of the damage caused by diabetes-associated complications, such as impaired cardiovascular health, one of the most common complications [32].

Prevalence of diabetic complications in this study was slightly higher among diabetic patients having poor glycemic control (87 [39.2%]) compared to their counterparts. A study done in Gondar Ethiopia, also found diabetic complications were higher among DM patients with poor glycemic control [33]. The commonest diabetic complication identified in this study was retinopathy (26.7%). Likewise, a case-control study conducted in Brazil revealed that retinopathy is predominant among DM patients with poor glycemic control [34]. Moreover, a follow-up study in the USA showed the association between the level of glucose and diabetic retinopathy, which indicated that controlling blood glucose level using rigorous treatment gave rise to delayed slow progression of diabetic retinopathy [35].

The lack of a relationship between educational status and poor glycemic control in this study is not consistent with the findings of previous studies [14, 15, 18, 36], which reported that no formal education was associated with poor glycemic control. The reason for this difference could be that the majority of patients in previous studies had no formal education, while in the current study, the majority (31.5%) of the patients had attained college and above. In addition to this, type of treatment (being on insulin treatment) does not show significant association with poor glycemic, which is not in line with studies done previously elsewhere [17, 26, 27, 37, 38]. This might be due to the majority (58.7%) of the patients in the current study were taking oral anti-diabetics. The other reason could be that type 2 diabetes patients are treated by insulin when their blood glucose level is not controlled by oral anti-diabetics.

Limitations of the study

The current study has its own limitations that should be acknowledged. The use of mean FBG over HbA1c is one limitation; thus possibly under estimate the prevalence of poor glycemic control. However, an effort was made to overcome this issue by taking the mean average of the last three consecutive visits for FBG measurements. In addition, the incompleteness of the patients’ charts is one of the shortcomings of this study since some items like co-morbidities were abstracted from the patient charts. Furthermore, the subjective nature of self-reported responses for some items might be limited by recall bias, and since the data collectors were health professionals, social desirability bias may also occur for some items.

Conclusion

The current study revealed that the prevalence of poor glycemic control and diabetic complications is noticeably high among diabetes patients. DM complications were found slightly higher among patients with poor glycemic control. Poor glycemic control showed significant association with longer duration of diabetes, lack of regular follow-up, low adherence to treatment, use of other alternative treatments, unsatisfactory patient-physician relations, and insufficient physical exercise. Therefore, we recommend considering developing educational programs that emphasize the importance of medication adherence. Regular follow-up and physical activity would be of great benefit in poor glycemic control. It is also paramount to enhance effective patient-provider relations and communication skills when counseling diabetic patients. Furthermore, considering consulting the patients regarding the use of other alternative treatments at each visit is also essential.

Supporting information

S1 Table. Glycemic control status and socio-demographic characteristics of the study participants attending diabetic clinic at public hospitals in Hadiya zone, Southern Ethiopia, 2019.

https://doi.org/10.6084/m9.figshare.20449119.

https://doi.org/10.1371/journal.pone.0282962.s001

(DOCX)

S2 Table. Diabetic complications and use of other alternative treatment among study participants attending diabetic clinic at public hospitals in Hadiya zone, Southern Ethiopia, 2019.

https://doi.org/10.6084/m9.figshare.20449296.

https://doi.org/10.1371/journal.pone.0282962.s002

(DOCX)

S3 Table. Bivariate analysis of socio-demographic and economic factors among type 2 diabetic patients at Public hospitals in Hadiya Zone, Southern Ethiopia, 2019.

https://doi.org/10.6084/m9.figshare.20449344.

https://doi.org/10.1371/journal.pone.0282962.s003

(DOCX)

S4 Table. Bivariate analysis of clinical factors among T2 DM adult out patients at public Hospitals in Hadiya Zone, Southern Ethiopia, 2019.

https://doi.org/10.6084/m9.figshare.20449371.

https://doi.org/10.1371/journal.pone.0282962.s004

(DOCX)

Acknowledgments

The authors would like to acknowledge data collectors and study participants.

References

1. Fauci AS. Harrison’s Principles of Internal Medicine. 18th edition. The McGraw- hill company; 2012.
2. Saeedi P, Petersohn I, Salpea P, Malanda B, Karuranga S, Unwin N, et al. Global and regional diabetes prevalence estimates for 2019 and projections for 2030 and 2045: Results from the International Diabetes Federation Diabetes Atlas, 9th edition. Diabetes Res Clin Pract. 2019;157:4–9.
- View Article
- Google Scholar
3. Saeedi P, Salpea P, Karuranga S, Petersohn I, Malanda B, Gregg EW, et al. Mortality attributable to diabetes in 20–79 years old adults, 2019 estimates: Results from the International Diabetes Federation Diabetes Atlas, 9th edition. Diabetes Res Clin Pract. 2020;162:1–4.
- View Article
- Google Scholar
4. Zeru MA, Tesfa E, Mitiku AA, Seyoum A, Bokoro TA. Prevalence and risk factors of type-2 diabetes mellitus in Ethiopia: systematic review and meta-analysis. Sci Rep. 2021;11:1–15.
- View Article
- Google Scholar
5. Abebe N, Kebede T, Addise D. Review Article Diabetes in Ethiopia 2000–2016 –prevalence and related acute and chronic complications; a systematic review. African J Diabetes Med. 2017;25:7–12.
- View Article
- Google Scholar
6. International Diabetes Federation (IDF) (2015) DIABETES ATLAS IDF. IDF Diabetes Atlas. Seventh Ed. 2015.
7. Yigazu DM, Desse TA. Glycemic control and associated factors among type 2 diabetic patients at Shanan Gibe Hospital, Southwest Ethiopia. BMC Res Notes. 2017;10:1–6.
- View Article
- Google Scholar
8. American Diabetes Association. Standards of medical care in diabetes. Diabetes Care. 2016;39:1–112.
- View Article
- Google Scholar
9. Morisky D, Green L, Levine D. Morisky Medication Adherence Scales (MMAS 8 item). Med Care. 1986;:1–2.
- View Article
- Google Scholar
10. Christina M, Van Der Feltz-c, Patricia VO, Harm W.J, Van M, Edwin DB Ret al. A patient-doctor relationship questionnaire (PDRQ-9) in primary care: development and psychometric evaluation. Gen Hosp Psychiatry. 2004;26:115–20. pmid:15038928
- View Article
- PubMed/NCBI
- Google Scholar
11. Toobert DJ, Hampson SE, Glasgow RE. The Summary of Diabetes Self-Care. Diabetes Care. 2000;23:943–50.
- View Article
- Google Scholar
12. Alzaheb RA, Altemani AH. The prevalence and determinants of poor glycemic control among adults with type 2 diabetes mellitus in Saudi Arabia. Dovepress. 2018;11:15–21. pmid:29430192
- View Article
- PubMed/NCBI
- Google Scholar
13. Appolinary RK, Emmanuel C. Predictors of poor glycemic control in type 2 diabetic patients attending public hospitals in Dar es Salaam. Anticancer Res. 2014;6:155–65.
- View Article
- Google Scholar
14. Fiseha T, Alemayehu E, Kassahun W, Adamu A, Gebreweld A. Factors associated with glycemic control among diabetic adult out-patients in Northeast Ethiopia. BMC Res Notes. 2018;11:4–9.
- View Article
- Google Scholar
15. Kassahun T, Eshetie T, Gesesew H. Factors associated with glycemic control among adult patients with type 2 diabetes mellitus: A cross-sectional survey in Ethiopia. BMC Res Notes. 2016;9:1–6.
- View Article
- Google Scholar
16. Fekadu G, Bula K, Bayisa G, Turi E, Tolossa T, Kasaye HK. Challenges and factors associated with poor glycemic control among type 2 diabetes mellitus patients at nekemte referral hospital, Western Ethiopia. J Multidiscip Healthc. 2019;12:963–74. pmid:31819470
- View Article
- PubMed/NCBI
- Google Scholar
17. Yohannes T, Adamu A, Tedla K, Wondimu A. Magnitude of glycemic control and its associated factors among patients with type 2 diabetes at Tikur Anbessa Specialized Hospital, Addis Ababa, Ethiopia. PLoS One. 2015;:1–13.
- View Article
- Google Scholar
18. Almutairi MA, Said SM, Zainuddin H. Predictors of Poor Glycemic Control Among Type Two Diabetic Patients. Am J M edicine M edical Sci. 2013;3:17–21.
- View Article
- Google Scholar
19. Ufuoma C, Godwin Y, Kester Ad, Ngozi Jc. Determinants of glycemic control among persons with type 2 diabetes mellitus in Niger Delta. Sahel Med J. 2016;19:190–5.
- View Article
- Google Scholar
20. UK Prospective Diabetes Study (UKPDS) Group. Intensive blood-glucose control with sulphonylureas or insulin compared with conventional treatment and risk of complications in patients with type 2 diabetes (UKPDS 33). Lancet. 1998;352 Ukpds 33:837–53.
- View Article
- Google Scholar
21. Bagonza J, Rutebemberwa E, Bazeyo W. Adherence to anti diabetic medication among patients with diabetes in eastern Uganda; A cross sectional study. BMC Health Serv Res. 2015;:1–7.
- View Article
- Google Scholar
22. Alhariri A, Daud F, Almaiman A, Ayesh S, Saghir M. Factors associated with adherence to diet and exercise among type 2 diabetes patients in Hodeidah city, Yemen. Diabetes Manag. 2017;7:264–71.
- View Article
- Google Scholar
23. Gonçalves da Silva D, Alberto Simeoni L, Amorim Amato A. Factors Associated with Poor Glycemic Control among Patients with Type 2 Diabetes in the Southeast Region of Brazil. Int J Diabetes Res. 2018;8:36–40.
- View Article
- Google Scholar
24. Khan AR, Lateef ZNA, Aithan MA Al, Bu-khamseen MA. Factors contributing to non-compliance among diabetics attending primary health centers in the Al Hasa district of Saudi Arabia. J Fam Community Med. 2012;19. pmid:22518355
- View Article
- PubMed/NCBI
- Google Scholar
25. Hana T, Ali Ei, Haya M, Medhat K. Adherence of Type-2 Diabetic Patients to Treatment Study questionnaires. Kuwait Med J. 2014.
- View Article
- Google Scholar
26. Abebe SM, Berhane Y, Worku A, Alemu S, Mesfin N. Level of sustained Glycemic control and associated factors among patients with diabetes mellitus in Ethiopia: A hospital-based cross-sectional study. Diabetes, Metab Syndr Obes Targets Ther. 2015;8:65–71. pmid:25657591
- View Article
- PubMed/NCBI
- Google Scholar
27. Ashur ST, Shah SA, Bosseri S, Fah TS, Shamsuddin K. Glycaemic control status among type 2 diabetic patients and the role of their diabetes coping behaviours: A clinic-based study in Tripoli, Libya. Libyan J Med. 2016;11:1–9. pmid:27005896
- View Article
- PubMed/NCBI
- Google Scholar
28. Abebe SM, Yemane B, Alemayehu W. Barriers to diabetes medication adherence in North West Ethiopia. SpringerOpen J. 2014;:1–6. pmid:24834373
- View Article
- PubMed/NCBI
- Google Scholar
29. Stephani V, Opoku D, Beran D. Self-management of diabetes in Sub-Saharan Africa: a systematic review. BMC Public Health. 2018;:1–11. pmid:30268115
- View Article
- PubMed/NCBI
- Google Scholar
30. Mekuria et al. Prevalence and correlates of herbal medicine use among type 2 diabetic patients in Teaching Hospital in Ethiopia: A cross-sectional study. BMC Complement Altern Med. 2018;:1–8.
- View Article
- Google Scholar
31. Endalew H, Wudineh HM, Tefera B, Zewdie B. Self-care practice and glycaemic control amongst adults with diabetes at the Jimma University Specialized Hospital in south-west Ethiopia: A cross-sectional study. Afr J Prim Heal Care Fam Med. 2012;:1–6.
- View Article
- Google Scholar
32. Zar Chi T, Srijit D LJ. Role of Exercise in the Management of Diabetes Mellitus: The Global Scenario. PLoS One. 2013;8:1–8.
- View Article
- Google Scholar
33. Fasil A, Biadgo B, Abebe M. Glycemic control and diabetes complications among diabetes mellitus patients attending at University of Gondar Hospital, Northwest Ethiopia. Diabetes, Metab Syndr Obes Targets Ther. 2019;12:75–83. pmid:30613158
- View Article
- PubMed/NCBI
- Google Scholar
34. Lima VC, Cavalieri GC, Lima MC, Nazario NO, Lima GC. Risk factors for diabetic retinopathy: A case-control study. Int J Retin Vitr. 2016;2:1–7. pmid:27847639
- View Article
- PubMed/NCBI
- Google Scholar
35. Aiello LP. Diabetic retinopathy and other ocular findings in the diabetes control and complications trial/epidemiology of diabetes interventions and complications study. Diabetes Care. 2014;37:17–23. pmid:24356593
- View Article
- PubMed/NCBI
- Google Scholar
36. Kayar Y, Ilhan A, Kayar NB, Unver N, Coban G, Ekinci I, et al. Relationship between the poor glycemic control and risk factors, life style and complications. Biomed Res. 2017;28:1581–6.
- View Article
- Google Scholar
37. Basu S, Garg S, Sharma N, Singh MM, Garg S. Adherence to self-care practices, glycemic status and influencing factors in diabetes patients in a tertiary care hospital in Delhi. World J Diabetes. 2018;9:72–9. pmid:29988911
- View Article
- PubMed/NCBI
- Google Scholar
38. Haghighatpanah M, Nejad ASM, Haghighatpanah M, Thunga G, Mallayasamy S. Factors that Correlate with Poor Glycemic Control in Type 2 Diabetes Mellitus Patients with Complications. Osong Public Heal Res Perspect. 2018;9:167–74. pmid:30159222
- View Article
- PubMed/NCBI
- Google Scholar

[ref1] 1. Fauci AS. Harrison’s Principles of Internal Medicine. 18th edition. The McGraw- hill company; 2012.

[ref2] 2. Saeedi P, Petersohn I, Salpea P, Malanda B, Karuranga S, Unwin N, et al. Global and regional diabetes prevalence estimates for 2019 and projections for 2030 and 2045: Results from the International Diabetes Federation Diabetes Atlas, 9th edition. Diabetes Res Clin Pract. 2019;157:4–9.
View Article
Google Scholar

[3] View Article

[4] Google Scholar

[ref3] 3. Saeedi P, Salpea P, Karuranga S, Petersohn I, Malanda B, Gregg EW, et al. Mortality attributable to diabetes in 20–79 years old adults, 2019 estimates: Results from the International Diabetes Federation Diabetes Atlas, 9th edition. Diabetes Res Clin Pract. 2020;162:1–4.
View Article
Google Scholar

[6] View Article

[7] Google Scholar

[ref4] 4. Zeru MA, Tesfa E, Mitiku AA, Seyoum A, Bokoro TA. Prevalence and risk factors of type-2 diabetes mellitus in Ethiopia: systematic review and meta-analysis. Sci Rep. 2021;11:1–15.
View Article
Google Scholar

[9] View Article

[10] Google Scholar

[ref5] 5. Abebe N, Kebede T, Addise D. Review Article Diabetes in Ethiopia 2000–2016 –prevalence and related acute and chronic complications; a systematic review. African J Diabetes Med. 2017;25:7–12.
View Article
Google Scholar

[12] View Article

[13] Google Scholar

[ref6] 6. International Diabetes Federation (IDF) (2015) DIABETES ATLAS IDF. IDF Diabetes Atlas. Seventh Ed. 2015.

[ref7] 7. Yigazu DM, Desse TA. Glycemic control and associated factors among type 2 diabetic patients at Shanan Gibe Hospital, Southwest Ethiopia. BMC Res Notes. 2017;10:1–6.
View Article
Google Scholar

[16] View Article

[17] Google Scholar

[ref8] 8. American Diabetes Association. Standards of medical care in diabetes. Diabetes Care. 2016;39:1–112.
View Article
Google Scholar

[19] View Article

[20] Google Scholar

[ref9] 9. Morisky D, Green L, Levine D. Morisky Medication Adherence Scales (MMAS 8 item). Med Care. 1986;:1–2.
View Article
Google Scholar

[22] View Article

[23] Google Scholar

[ref10] 10. Christina M, Van Der Feltz-c, Patricia VO, Harm W.J, Van M, Edwin DB Ret al. A patient-doctor relationship questionnaire (PDRQ-9) in primary care: development and psychometric evaluation. Gen Hosp Psychiatry. 2004;26:115–20. pmid:15038928
View Article
PubMed/NCBI
Google Scholar

[25] View Article

[26] PubMed/NCBI

[27] Google Scholar

[ref11] 11. Toobert DJ, Hampson SE, Glasgow RE. The Summary of Diabetes Self-Care. Diabetes Care. 2000;23:943–50.
View Article
Google Scholar

[29] View Article

[30] Google Scholar

[ref12] 12. Alzaheb RA, Altemani AH. The prevalence and determinants of poor glycemic control among adults with type 2 diabetes mellitus in Saudi Arabia. Dovepress. 2018;11:15–21. pmid:29430192
View Article
PubMed/NCBI
Google Scholar

[32] View Article

[33] PubMed/NCBI

[34] Google Scholar

[ref13] 13. Appolinary RK, Emmanuel C. Predictors of poor glycemic control in type 2 diabetic patients attending public hospitals in Dar es Salaam. Anticancer Res. 2014;6:155–65.
View Article
Google Scholar

[36] View Article

[37] Google Scholar

[ref14] 14. Fiseha T, Alemayehu E, Kassahun W, Adamu A, Gebreweld A. Factors associated with glycemic control among diabetic adult out-patients in Northeast Ethiopia. BMC Res Notes. 2018;11:4–9.
View Article
Google Scholar

[39] View Article

[40] Google Scholar

[ref15] 15. Kassahun T, Eshetie T, Gesesew H. Factors associated with glycemic control among adult patients with type 2 diabetes mellitus: A cross-sectional survey in Ethiopia. BMC Res Notes. 2016;9:1–6.
View Article
Google Scholar

[42] View Article

[43] Google Scholar

[ref16] 16. Fekadu G, Bula K, Bayisa G, Turi E, Tolossa T, Kasaye HK. Challenges and factors associated with poor glycemic control among type 2 diabetes mellitus patients at nekemte referral hospital, Western Ethiopia. J Multidiscip Healthc. 2019;12:963–74. pmid:31819470
View Article
PubMed/NCBI
Google Scholar

[45] View Article

[46] PubMed/NCBI

[47] Google Scholar

[ref17] 17. Yohannes T, Adamu A, Tedla K, Wondimu A. Magnitude of glycemic control and its associated factors among patients with type 2 diabetes at Tikur Anbessa Specialized Hospital, Addis Ababa, Ethiopia. PLoS One. 2015;:1–13.
View Article
Google Scholar

[49] View Article

[50] Google Scholar

[ref18] 18. Almutairi MA, Said SM, Zainuddin H. Predictors of Poor Glycemic Control Among Type Two Diabetic Patients. Am J M edicine M edical Sci. 2013;3:17–21.
View Article
Google Scholar

[52] View Article

[53] Google Scholar

[ref19] 19. Ufuoma C, Godwin Y, Kester Ad, Ngozi Jc. Determinants of glycemic control among persons with type 2 diabetes mellitus in Niger Delta. Sahel Med J. 2016;19:190–5.
View Article
Google Scholar

[55] View Article

[56] Google Scholar

[ref20] 20. UK Prospective Diabetes Study (UKPDS) Group. Intensive blood-glucose control with sulphonylureas or insulin compared with conventional treatment and risk of complications in patients with type 2 diabetes (UKPDS 33). Lancet. 1998;352 Ukpds 33:837–53.
View Article
Google Scholar

[58] View Article

[59] Google Scholar

[ref21] 21. Bagonza J, Rutebemberwa E, Bazeyo W. Adherence to anti diabetic medication among patients with diabetes in eastern Uganda; A cross sectional study. BMC Health Serv Res. 2015;:1–7.
View Article
Google Scholar

[61] View Article

[62] Google Scholar

[ref22] 22. Alhariri A, Daud F, Almaiman A, Ayesh S, Saghir M. Factors associated with adherence to diet and exercise among type 2 diabetes patients in Hodeidah city, Yemen. Diabetes Manag. 2017;7:264–71.
View Article
Google Scholar

[64] View Article

[65] Google Scholar

[ref23] 23. Gonçalves da Silva D, Alberto Simeoni L, Amorim Amato A. Factors Associated with Poor Glycemic Control among Patients with Type 2 Diabetes in the Southeast Region of Brazil. Int J Diabetes Res. 2018;8:36–40.
View Article
Google Scholar

[67] View Article

[68] Google Scholar

[ref24] 24. Khan AR, Lateef ZNA, Aithan MA Al, Bu-khamseen MA. Factors contributing to non-compliance among diabetics attending primary health centers in the Al Hasa district of Saudi Arabia. J Fam Community Med. 2012;19. pmid:22518355
View Article
PubMed/NCBI
Google Scholar

[70] View Article

[71] PubMed/NCBI

[72] Google Scholar

[ref25] 25. Hana T, Ali Ei, Haya M, Medhat K. Adherence of Type-2 Diabetic Patients to Treatment Study questionnaires. Kuwait Med J. 2014.
View Article
Google Scholar

[74] View Article

[75] Google Scholar

[ref26] 26. Abebe SM, Berhane Y, Worku A, Alemu S, Mesfin N. Level of sustained Glycemic control and associated factors among patients with diabetes mellitus in Ethiopia: A hospital-based cross-sectional study. Diabetes, Metab Syndr Obes Targets Ther. 2015;8:65–71. pmid:25657591
View Article
PubMed/NCBI
Google Scholar

[77] View Article

[78] PubMed/NCBI

[79] Google Scholar

[ref27] 27. Ashur ST, Shah SA, Bosseri S, Fah TS, Shamsuddin K. Glycaemic control status among type 2 diabetic patients and the role of their diabetes coping behaviours: A clinic-based study in Tripoli, Libya. Libyan J Med. 2016;11:1–9. pmid:27005896
View Article
PubMed/NCBI
Google Scholar

[81] View Article

[82] PubMed/NCBI

[83] Google Scholar

[ref28] 28. Abebe SM, Yemane B, Alemayehu W. Barriers to diabetes medication adherence in North West Ethiopia. SpringerOpen J. 2014;:1–6. pmid:24834373
View Article
PubMed/NCBI
Google Scholar

[85] View Article

[86] PubMed/NCBI

[87] Google Scholar

[ref29] 29. Stephani V, Opoku D, Beran D. Self-management of diabetes in Sub-Saharan Africa: a systematic review. BMC Public Health. 2018;:1–11. pmid:30268115
View Article
PubMed/NCBI
Google Scholar

[89] View Article

[90] PubMed/NCBI

[91] Google Scholar

[ref30] 30. Mekuria et al. Prevalence and correlates of herbal medicine use among type 2 diabetic patients in Teaching Hospital in Ethiopia: A cross-sectional study. BMC Complement Altern Med. 2018;:1–8.
View Article
Google Scholar

[93] View Article

[94] Google Scholar

[ref31] 31. Endalew H, Wudineh HM, Tefera B, Zewdie B. Self-care practice and glycaemic control amongst adults with diabetes at the Jimma University Specialized Hospital in south-west Ethiopia: A cross-sectional study. Afr J Prim Heal Care Fam Med. 2012;:1–6.
View Article
Google Scholar

[96] View Article

[97] Google Scholar

[ref32] 32. Zar Chi T, Srijit D LJ. Role of Exercise in the Management of Diabetes Mellitus: The Global Scenario. PLoS One. 2013;8:1–8.
View Article
Google Scholar

[99] View Article

[100] Google Scholar

[ref33] 33. Fasil A, Biadgo B, Abebe M. Glycemic control and diabetes complications among diabetes mellitus patients attending at University of Gondar Hospital, Northwest Ethiopia. Diabetes, Metab Syndr Obes Targets Ther. 2019;12:75–83. pmid:30613158
View Article
PubMed/NCBI
Google Scholar

[102] View Article

[103] PubMed/NCBI

[104] Google Scholar

[ref34] 34. Lima VC, Cavalieri GC, Lima MC, Nazario NO, Lima GC. Risk factors for diabetic retinopathy: A case-control study. Int J Retin Vitr. 2016;2:1–7. pmid:27847639
View Article
PubMed/NCBI
Google Scholar

[106] View Article

[107] PubMed/NCBI

[108] Google Scholar

[ref35] 35. Aiello LP. Diabetic retinopathy and other ocular findings in the diabetes control and complications trial/epidemiology of diabetes interventions and complications study. Diabetes Care. 2014;37:17–23. pmid:24356593
View Article
PubMed/NCBI
Google Scholar

[110] View Article

[111] PubMed/NCBI

[112] Google Scholar

[ref36] 36. Kayar Y, Ilhan A, Kayar NB, Unver N, Coban G, Ekinci I, et al. Relationship between the poor glycemic control and risk factors, life style and complications. Biomed Res. 2017;28:1581–6.
View Article
Google Scholar

[114] View Article

[115] Google Scholar

[ref37] 37. Basu S, Garg S, Sharma N, Singh MM, Garg S. Adherence to self-care practices, glycemic status and influencing factors in diabetes patients in a tertiary care hospital in Delhi. World J Diabetes. 2018;9:72–9. pmid:29988911
View Article
PubMed/NCBI
Google Scholar

[117] View Article

[118] PubMed/NCBI

[119] Google Scholar

[ref38] 38. Haghighatpanah M, Nejad ASM, Haghighatpanah M, Thunga G, Mallayasamy S. Factors that Correlate with Poor Glycemic Control in Type 2 Diabetes Mellitus Patients with Complications. Osong Public Heal Res Perspect. 2018;9:167–74. pmid:30159222
View Article
PubMed/NCBI
Google Scholar

[121] View Article

[122] PubMed/NCBI

[123] Google Scholar

Figures

Abstract

Background

Methods

Results

Conclusion

Introduction

Materials and methods

Study design, area, and study period

Population

Sample size and sampling technique

Data collection procedure

Measurements and operational definition

Data management and quality assurance

Statistical analysis

Ethical considerations

Results

Socio-demographic characteristics of the respondents

Glycemic control status

Diabetes complications

Clinical characteristics of T2 DM patients

Knowledge and attitude towards diabetic care

Factors associated with glycemic control

Discussion

Limitations of the study

Conclusion

Supporting information

S1 Table. Glycemic control status and socio-demographic characteristics of the study participants attending diabetic clinic at public hospitals in Hadiya zone, Southern Ethiopia, 2019.

S2 Table. Diabetic complications and use of other alternative treatment among study participants attending diabetic clinic at public hospitals in Hadiya zone, Southern Ethiopia, 2019.

S3 Table. Bivariate analysis of socio-demographic and economic factors among type 2 diabetic patients at Public hospitals in Hadiya Zone, Southern Ethiopia, 2019.

S4 Table. Bivariate analysis of clinical factors among T2 DM adult out patients at public Hospitals in Hadiya Zone, Southern Ethiopia, 2019.

Acknowledgments

References