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The incidence and predictors of poor glycemic control among adults with type 2 diabetes mellitus in ambulatory clinic of mettu karl referral hospital, southwestern, Ethiopia: a prospective cross sectional study

Gudisa Bereda

SWAN diagnostic pharmaceutical importer, Addis Ababa, Ethiopia

E-mail : bhuvaneswari.bibleraaj@uhsm.nhs.uk

Gemechis Bereda

SWAN diagnostic pharmaceutical importer, Addis Ababa, Ethiopia

DOI: 10.15761/DU.1000155

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Abstracts

Background: Diabetes mellitus refers to a grouping of metabolic diseases involving prolonged hyperglycemia caused by the inadequate secretion of insulin, poor insulin action, or a combination of the two. Poor glycaemic control is a major public health problem among patients with type 2 diabetes mellitus.

Objective: To expose the incidence and predictors of poor glycemic control among adults with type 2 diabetes mellitus in ambulatory clinic of Mettu Karl Referral Hospital.

Methods: An institutional based prospective cross-sectional survey was carried out from April 23/2020 to June 24/2021.Data was collected through employing structured questioner, and then the collected data was cleared, coded and analyzed by statistical packages for social sciences 25.0 version statistical software. Descriptive statistics such as the frequency and percentage were used. Those variables with p- value less than 0.25 in bi-variable analysis were entered into multivariable analysis. A p-value of less than 0.05 was considered significant.

Results: A total of 122 patients with type 2 diabetes mellitus were included in this study. The overall incidence of poor glycemic control among type 2 diabetic patients was 60.7%. Poor glycemic control was significantly associated with older age (AOR= 2.98,95%CI:1.089-2.023; P=0.034), uneducated patients(AOR=5.075,95%CI:1.957-3. 649;p=0.009), Glibenclamide+metformin drug regimen (AOR=3.95,95%CI:1.429-3. 750;p=0.018),Low adherance (AOR=2.68,95%CI:1.764-4.928;p=0.002),cigarette smokers social habit (AOR=1.49,95%CI:2.034-3.864;p=0.008),patents who had comorbidities (AOR=2.5,95%CI:1.967-5.497;p =0.028), and patients who had nephropathic complication of diabetes(AOR=6.45,95%CI:3.071-17.632;p=0.005) were the significantly associated predictors of poor glycemic control.

Conclusion and recommendation: Our study investigated the prevalence of poor glycemic control among type 2 diabetic patients was high. About half of the patients were on anti-diabetic medication for between one to four years and slightly less than half of oral hypoglycemic agents were most prescribed drug regimen. Health care workers should have to advice the patients about life style modification and on how they take their medication.

Keywords

type 2 diabetes mellitus, risk factors, poor glycemic control, ambulator y clinic, mettu karl referral hospital, ethiopia

Abbreviations

ADA: American Diabetes Association; BMI: Body Mass Index; DM: Diabetes Mellitus; FPS: Fasting Plasma Sugar; HbA1c: Glycated Hemoglobin; HTN: Hypertension; MKRH: Mettu Karl Referral Hospital; SSA: Sub-Saharan Africa; T2DM: Type 2 diabetes mellitus; WHO: World Health Organization.

Introduction

Diabetes mellitus is a serious, chronic metabolic disorders that characterized by high sugar level either when the pancreas does not produce enough insulin, or when the body cannot effectively use insulin. Type 2 diabetes mellitus (T2DM) accounts about 90% of all diagnosed cases of diabetes among adults [1]. Globally,8.8% (415 million) of adults suffered from diabetes in 2015,and it is estimated that 652 million people (10.4%) will have diabetes by 2040.The World Health Organization (WHO) reported that high blood glucose level due to diabetes is the third highest risk factor for premature mortality after high blood pressure and tobacco use [2]. More than 77 % of morbidity and 88% of mortality due to DM occur in low and middle-income countries. In Ethiopia, the prevalence of diabetes was 3.5 % in 2011 [3]. Type 2 diabetes mellitus (T2DM) is the most common form of DM, accounting for more than 90 % of cases. Control of diabetes is more than just taking medicine other aspects of self-management such as self-monitoring of blood glucose, dietary restrictions, regular foot care and ophthalmic examination have all been shown to markedly reduce the incidence and progression of diabetes complications [4]. The major risk factors in the development of T2DM are family history, obesity, race/ethnicity, age increment (≥40year), previous identified impaired fasting glucose or impaired glucose tolerance, hypertension (HTN), hyperlipidemia and history of gestational DM [5]. In Ethiopia, the prevalence of diabetes admission has increased from 1.9% in 1970 to 9.5% in 1999 of all medical admissions most importantly uncontrolled blood glucose due to non-compliance to anti-diabetic medications [6]. The American Diabetes Association (ADA) has designated HbA1c level of <7% as a goal of optimal blood glucose control and the American Association of Clinical Endocrinologist has further recommended HbA1c level of <6.5% [7]. Controlling the glycemic level is considered the main therapeutic intervention to prevent diabetes complications and further organ damage. Healthcare systems in sub-Saharan Africa (SSA) also vary widely [8]. There is poor health seeking behaviors in low resource countries because of inaccessible quality healthcare that increases the risk of DM complications. The management of DM is complex, and good glycemic control significantly reduces the risk of complications [9]. The goal of treatment for DM is to prevent mortality and complications by normalizing blood glucose level. But blood glucose level might be increased despite appropriate therapy resulting in complications, such as disturbances in fat metabolism, nerve damage, and eye disease [10].

Type 2 diabetes constitutes about 85–95% of all diabetes in high-income countries with a higher percentage in low and middle-income countries due to rapid socio- cultural changes, ageing populations, increasing urbanization, reduced physical activity and unhealthy lifestyle and behavioral patterns. It is a leading cause of blindness, end stage renal disease and stroke. These complications are two to five times more common among diabetic patients. Type 2 diabetes is associated with increased morbidity and mortality compared with the general population [11]. High glycemic control is difficult to achieve, and prior research has reported many factors as contributing to poor control among patients, including their age, gender, level of education, weight, smoking status, marital status, the duration of diabetes, the medications taken, and numerous other factors [12]. However, it has been proved difficult to confirm exactly which of these factors are most directly associated with poor glycemic control. The World Health Organization (WHO) reported that high blood glucose level due to diabetes is the third highest risk factor for premature mortality after high blood pressure and tobacco use [13]. Diabetes is attributed to 14.5% of all-cause mortality among adults, and half of these deaths occur in adults under the age of 60 years. Nonetheless, diabetic complications are a major cause of disability and reduced quality of life. The estimated total global health expenditure due to diabetes is $673 billion in 2015, and it will reach $802 billion in 2030 [14]. Previous findings in Ethiopia also reported that the rate of poor glycemic control was high [15], most importantly due to non-compliance to existing medications.32The prevalence of poor glycemic control is paramount. A study done in Malaysia [16], 2015 showed that 72 % of patients had poor glycemic control, and two third of DM patients in Ethiopia [17] also had poor control. Previous studies assured that poor glycemic control correlated with enlarged risk of visual impairment, enlarged risk of kidney failure, and enlarged risk of cardiovascular disease [18]. This study will provide information for health-care providers and policymakers as a baseline for further study and determining the risk factors of poor glycemic control is important for its urgent management and further reduction of health-care costs related to the care needed.

Materials and methods

Study area, design and period

An institutional based prospective cross-sectional survey was conducted from April 23/2020 to June 24/2021, in the ambulatory clinic at Mettu Karl Referral Hospital, which located at 600 km from Addis Ababa.

Study participants

All type 2 diabetes patients who visited the ambulatory clinic of MKRH during the data collection period & that fulfilled the inclusion criteria was target population. Those aged 18 years or older, Patients who were on anti-diabetic medication(s) treatment for at least 6 months, Patients with at least three consecutive blood glucose, Measurements for 3 months, and patients who consented to participate were included in the study. Newly diagnosed, very sick patients, and those with physical or mental handicaps, Patients with hearing problems and previously diagnosed psychiatric were excluded.

Sample size calculation and sampling technique

The sample size was determined by using the single population proportion formula: The sample size was determined based on “P” value which was taken from JUSH, Southwest Ethiopia, P=0.709, or 70.9% n=((Za/2)2 P(1-P))/d2,n= sample size, P=prevalence of poor glycemic control ,d=margin of sampling error tolerated, z=the standard normal value at confidence interval of 95%. n=(1.96)2(1- 0.709) x (0.709) /(0.05)2=317. Since the total number of type 2 diabetes mellitus patients was less than 10,000,reduction formula(correction formula) were applied as follow nf = n/ (1+(n/N)), nf =317/(1+ (317/170)=111.When 10% contingency is added to minimize non response rate,then final sample size was found to be 122.Purposive sampling technique was used to recruit samples for the study in each day of the data collection process until the desired sample size was obtained.

Study variables

Dependent variable was poor glycemic control among adults with type 2 diabetes mellitus, and independent variable were Socio demographic factors (age, sex, educational status, monthly income, marital status, family size), Clinical characteristics (family histories of diabetes, the duration of disease, and self-reported comorbidities), Life style of patients’(smoking status, exercise per day and dietitians (which restricted their intakes of sugar, salt, and fat),Medications the patients were taking to manage their diabetes, and whether they self-monitored their blood glucose levels.

Data extraction and procedure

Data was collected from the medical cards to know their blood glucose level and patients were interviewed by using a semi-structured questionnaire developed by reviewing different literature's. The data collection format contained four parts. The first part of the questionnaire involved socio-demographic data on the participating patients’ age, marital status, gender, residence, education level, employment status, and income. The second part concerned their clinical characteristics, including family histories of diabetes, the duration of disease, and self-reported comorbidities. The third part gathered lifestyle data on the patients’ smoking status, whether they exercised regularly (i.e., whether they were involved in at least 30 minutes of exercise per day, at least 3 days per week), and whether they followed a set dietary plan approved by dietitians (which restricted their intakes of sugar, salt, and fat).The fourth and final part had questions on the medications the patients were taking to manage their diabetes, and whether they self-monitored their blood glucose levels. The weight of each patient were measured by using BMI=kilogram of the patients(kg)/ height of patients(m2). Based on the calculated BMI, the patients were divided into categories reflecting the World Health Organization (WHO)’s definitions: normal range (BMI =18.5–24.9 kg/m2,overweight (BMI =25–29.9 kg/m2,and obese (BMI ≥30 kg/m2.Glycemic control was based on American Diabetic Association (ADA) recommendation into two groups as good glycemic control with fasting blood glucose of 70–130 mg/dL and poor glycemic control with fasting blood glucose of <70 mg/dL and >130 mg/dL.

Data processing and analysis

The screened data was coded and analyzed through employing statistical packages for social sciences 25.0 version statistical software. Data are presented as the mean± standard deviation (SD) for continuous variables and proportions for categorical variables. Chi-square and bi variate logistic regression analysis was conducted to see the existence of odds association and select candidate variables with P value below 0.25 were considered to multivariable logistic regression. A 95% CI and p-value of <0.05 was considered to be statistically significant.

Data quality assurance

All steps in data collection and recording were closely monitored by the principal investigator and daily collected data was, recorded and compiled for the next day study. Finally, the data collected will be checked for completeness and consistency on daily basis

Ethical considerations

A formal letter was obtained from SWAN diagnostic pharmaceutical importer and official letter of co-operations was provided to mettu karl referral hospital prior to data collection. Patient consent was obtained prior to data collection and no personal identity was disclosed. The instruments and procedure were not cause any harm to the study subject. Thus, name and address of the patient was not recorded in data collection checklist.

Operational Definitions

Poor glycemic control was operationally defined if fasting blood glucose (FBG) level was above 130 mg/dl.

Results

Socio-demographic characteristics of the study participants

A total of 122 type 2 diabetic patients were included in this study, of whom 67 (54.9%) were male. The largest age group was >40 years which accounted for 66 (54.1%). A majority 72(59.0%)of patients were live in rural area and 79(64.8%) were earn monthly income ≤500 ETB. Majority 79(64.8%) of patients were married and 43 (35.2%) of patients were uneducated. Preponderance 38(31.1%) of patients had social habit which mostly accounted for cigarette smokers and 30(24.6%) had now social habit. A majority 77(63.1%) of patients had no family history. The overall incidence of poor glycemic control among type 2 diabetic patients was 74(60.7%) (Table 1).

Table 1. Socio-demographic characteristics of the study of T2DM patients in Mettu Karl Referral Hospital, South-western, Ethiopia, 2021

Variables

Category

Frequency

Percent

Age

≤40 years

56

45.9

>40 years

66

54.1

Sex

Male

67

54.9

Female

55

45.1

Residency

Urban

50

41.0

Rural

72

59.0

Monthly income

≤ 500 ETB

79

64.8

>500 ETB

43

35.2

Marital status

Unmarried

43

35.2

Married

79

64.8

Educational status

Uneducated

45

36.9

Primary

39

32.0

Secondary

27

22.1

Higher education

11

9.0

Social habit

Cigarette smokers

38

31.1

Alcohol drinker

32

26.2

Khat chewing

22

18.0

None

30

24.6

Family history

Yes

45

36.9

No

77

63.1

Magnitude of poor glycemic control

Yes

74

60.7

No

48

393

Clinical characteristics and disease related characteristics

A majority 42(34.4%) of the respondents were overweight. Great majority 89(73.0%) of participants had >130gm/dl fasting blood sugar and 78(63.9%) had <140/90 mmHg blood pressure. Regarding adherance 56(45.9%),38(31.1%),28 (23.0%) was low, moderate and high respectively. Above half 67(54.9%) of type 2 diabetic patients were had at least one comorbidities and 32(26.2%) had nephropathy diabetic complication. Hypertension 55(45.1%) was the most present comorbidities followed by renal disease 29(23.8%). Majority 89(73.0%) of study participants were pursue pharma cological only rather they use nonpharmacological treatment (Table 2).

Table 2. Clinical characteristics and disease related variables among T2DM patients in Mettu Karl Referral Hospital, South-western, Ethiopia, 2021

Variables

Category

Frequency

Percent

Body mass index

<18.5 kg/m2

18

14.8

18.5–24.9 kg/m2

30

24.6

25–29.9 kg/m2

42

34.4

≥30 kg/m2

32

26.2

Fasting blood sugar

≤ 130gm/dl

33

27.0

>130gm/dl

89

73.0

Blood pressure

<140/90 mmHg

78

63.9

≥ 140/90 mmHg

44

36.1

Adherance

Low

56

45.9

Moderate

38

31.1

High

28

23.0

Co-morbidities

Yes

67

54.9

No

55

45.1

Complication

Retinopathy

16

13.1

Cardiac complications

17

13.9

Nephropathy

32

26.2

Neuropathy

12

9.8

None

45

36.9

Type of co-morbidities

Hypertension

55

45.1

DKA

5

4.1

Renal disease

21

17.2

Peripheral neuropathy

29

23.8

Other

12

9.8

Type of treatment

Non-pharmacological

33

27.0

Pharmacological

89

73.0

Medication related and lifestyle related characteristics

About half 62(50.8%) of the patients were on anti-diabetic medication for between 1-4 years and slightly above one half 68(55.8%) of oral hypoglycemic agents were most prescribed drug type. Metformin 41(33.6%) was the mostly recommended drugs followed by Metformin and NPH insulin 34(27.9%). Above half 77(63.1%) of patients had ≤2 number drugs they take and less than half 50(41.0%) of patients had at least one concomitant medication. Enalapril 21(42%) most concomitant medication administered followed by Enalapril+ASA 16(32%). Above half 66(54.1%) of patients had inadequate health diet and 79(64.8%) hadn’t do physical exercise. A majority 95 (77.9%) of participants had not care their foot and 87(71.3%) had not have self- monitoring blood glucose (Table 3).

Table 3. Medication related and life style related characteristics among T2DM patient s in Mettu Karl Referral Hospital, South-western, Ethiopia, 2021

Variables

Category

Frequency

Percent

Duration of treatment

1-4 years

62

50.8

5-10 years

43

35.2

> 10 years

17

13.9

Drug regimen

Oral hypoglycemic agents

87

71.3

Oral hypoglycemic agents+ Insulin

35

28.7

Type of DM drugs

Metformin

41

33.6

Glibenclamide and metformin

19

15.6

Glibenclamide

17

13.9

Metformin and NPH insulin

34

27.9

Metformin+Glibenclamide+ insulin

11

9.0

Numbers of drugs tak en

≤2 drugs

77

63.1

> 2 drugs

45

36.9

Concomitant medicat ion

Yes

50

41.0

No

72

59.0

Type of concomitant medication

Enalapril

21

42.0

Enalapril + ASA

16

32.0

Enalapril + ASA + atenolol

9

18.0

Enalapril+ASA+hydrochlorothiazide

4

8.0

Health diet

Adequate

56

45.9

Inadequate

66

54.1

Physical exercise

Yes

43

35.2

No

79

64.8

Foot care

Yes

27

22.1

No

95

77.9

Self monitoring bloo d glucose

Yes

35

28.7

No

87

71.3

Logistic regression analysis of the association between independent variables and poor glycemic control among T2DM

The relative odds of poor glycemic control was 2.98-times (AOR=2.98,95%CI=1.089 -2.023, P=0.034) higher among patients in the age ≤40 years compared to the ages of greater than 40 years. Regarding educational status uneducated patients were 1.75 more likely had poor glycemic control(AOR=1.75,95%CI=1.957-3.649,P=0.009) than primary, secondary and higher educational status. Patients who take Glibenclamide and metformin drug regimen were 3.95 more likely had poor glycemic control (AOR=3.95,95%CI=1.967-9.645, P=0.018) than those who taken others regimen. Low adherance were 2.68 more likely had poor glycemic control (AOR=2.68,95% CI=1.967-9.645,P=0.002) than moderate and high adherance. Patients who whose cigarette smokers social habit were 1.49 more likely had poor glycemic control (AOR=1.49,95%CI=1.967-9.645,P=0.008) than those who had others social habit. Patents who had comorbidities were 2.5 more likely have poor glycemic control (AOR=2.5,95% CI=1.967-5.497, P=0.028) than who hadn’t comorbidities. Participant who had nephropathic complication of diabetes were 6.45 more likely had poor glycemic control (AOR=6.45,95%CI=1.967-5.497, P=0.005) than those who had others complication (Table 4).

Table 4. Logistic regression analysis of the association between independent variables and poor glycemic control among T2DM patients in Mettu Karl Referral Hospital South-western, Ethiopia, 2021

Variables

Category

n(%)

AOR (95% C.I)

P-value

Age

≤40 years

56(45.9)

2.98(1.089-2.023)

0.034

>40 years

66(54.1)

1

Sex

Male

67(54.9)

1.96(1.043-1.848)

0.078

Female

55(45.1)

1

Educational status

Uneducated

45(36.9)

1.75(1.957-3.649)

0.009

Primary

39(32.0)

1.01(1.968-1.967)

0.869

Secondary

27(22.1)

0.364(0.067-1.028)

0.184

Higher education

11(9.0)

1

Type of DM dr ugs

Metformin

41(33.6.0)

1.873(1.921-2.340)

0.09

Glibenclamide and metformin

19(15.6)

1.043(1.429-3.750)

0.018

Glibenclamide

17(13.9)

0.740(0.694-1.947)

0.873

Metformin and NP H insulin

34(27.9)

1.75(1.967-2.645)

0.095

Metformin+ Insulin + Glibenclamide 

11(9.0)

1

Adherance

Low

56(45.9)

2.68(1.764-4.928)

0.002

Moderate

38(31.1)

1.146(1.437-2.746)

0.645

High

28(23.0)

1

Social habit

Cigarette smokers

38(31.1)

1.978(2.034-3.864)

0.008

Alcohol drinker

32(26.2)

1.34(1.564-2.853)

0.07

Khat chewing

22(18.0)

5.68(2.968-12.476)

0.061

None

30(24.6)

1

Comorbidity

Yes

67(54.9)

2.5(1.967-5.497)

0.028

No

55(45.1)

1

Duration of tre atment

1-4 years

62(50.8)

0.478(0.021-1.017)

0.476

5-10 years

43(35.2)

2.15(1.967-4.231)

0.005

> 10 years

17(13.9)

1

Residency

Urban

50(41.0)

1.254(1.694-2.078)

0.045

Rural

72(59.0)

1

Type of compli cation

Retinopathy

16(13.1)

0.285(0.047-1.074)

0.178

Neuropathy

17(13.9)

1.476(1.967-2.863)

0.710

Nephropathy

32(26.2)

6.45(3.071-17.632)

0.095

Cardiac complicatio ns

12(9.8)

1.435(1.849-2.147)

0.453

None

45(36.9)

1

Discussion

Patients with diabetes have a 2-to-4-fold increase in the risk of both cardiovascular and cerebrovascular disease, resulting in an increased mortality rate among patients with diabetes compared to the general population [19]. The main goal of diabetes management is to ensure optimal glycemic control.Poorly controlled T2DM results in increased rates of micro and macrovascular diabetic complications which in turn lead to increased healthcare costs [20].

The present study revealed that the overall prevalence of poor glycemic control among type 2 diabetic patients was 60.7% were lower than study conducted in Military Hospital in Hodeidah 73.2%,Ethiopia 64.72%,Bangladesh 82%,Saudi Arabia 74.9%,Kuwait 78.8% [21-25].The differences was due to delay in the begging and intensification of unnecessarily and poor adherance to anti-diabetic treatments and also include less life style modification which perhaps no health diet, and low physical exercise. Our study was in line with the study conducted in Middle East and the Horn of Africa 61.1%, Shanan Gibe hospital 59.2% [26,27]. This similarity was due to in sub-saharan Africa patients may not acquire their medication because they earn low monthly income and rural area residents patients had not got more education about disease burden and medication due to they far from social media and health center. The current study were higher than Saudi Arabia 50%,china 50.3%,Zimbabwe 58.2% [28-30]. This is because in our study diabetic patients were educated in the hospital how they use their medication somewhat.

In our study the incidence of poor glycemic control were observed in older ages > 40 years perhaps consistent with the study done in Bangladesh [24] which revealed that the prevalence of DM was more among old age group. This is because older adults were at high risk for the development of diabetic mellitus due to the combined effects of increasing insulin resistance and impaired pancreatic islet function with aging. And older agents are most vulnerable population, so diabetes increases the risk of falls, urinary incontinence, dementia, depression, vision and hearing loss. Besides, more likely to have functional limitations and report disability.

In our study uneducated type 2 diabetic patients had more poor glycemic control than primary, secondary, higher educational level were consistent with the study employed in Ethiopia [31] which displayed the significant difference of poor glycemic control was observed among illiterates than college/university graduates. This is because uneducated patients had no more hint on how and when to take the medication, how to monitor self-blood glucose sugar, how to take care for themselves and the no use balanced program of exercise and rest which help him/her keep blood sugar stable. Due lack comprehend they didn’t use carbohydrate as snack when they feel weak.

The current study observed that males were at higher risk to developing poor glycemic control than females were inline with the study done in a Suburban Tertiary Hospital in North-Western Nigeria [32] which observed that males were at higher risk of having poor glycaemic control compared to females. The reason whose males store more fat in their bellies, plasma levels of low density lipoprotein (bad cholesterol) and triglycerides were high in males, and males had smoking cigarette, being overweight, avoiding physical activity.

The present showed 63.1%patients had at least one complication. Here Nephropathy were the most commonly occurred diabetic complication and Neuropathy were the least occurred diabetic complication were higher than the study conducted in Tertiary Hospital in Northeast Ethiopia [33] which revealed that 59.7% of diabetic patients had at least one diabetic complication. The current survey were lower than the study conducted in Jimma, Ethiopia, where 83.0%. Because diabetic nephropathy was a common complication of type I and type II diabetes. Overtime poorly control diabetes can cause damage to blood vessels clusters in the kidney that filter waste from the body.

The relative odds of poor glycemic control was 2.98-times (AOR=2.98,95%CI=1.089 -2.023, P=0.034) higher among patients in the age ≤40 years compared to the ages of greater than 40 years. Regarding educational status uneducated patients were 1.75 more likely had poor glycemic control (AOR=1.75,95%CI=1.957-3.649, P=0.009) than primary, secondary and higher educational status. Patients who take Glibenclamide and metformin drug regimen were 3.95 more likely had poor glycemic control (AOR=3.95,95%CI=1.967-9.645,P=0.018)than those who taken others regimen. Low adherance were 2.68 more likely had poor glycemic control (AOR=2.68,95% CI=1.967-9.645, P=0.002) than moderate and high adherance. Patients who whose cigarette smokers social habit were 1.49 more likely had poor glycemic control (AOR=1.49,95%CI=1.967-9.645,P=0.008) than those who had others social habit. Patents who had comorbidities were 2.5 more likely have poor glycemic control (AOR=2.5,95% CI=1.967-5.497, P=0.028) than who hadn’t comorbidities. Participant who had nephropathic complication of diabetes were 6.45 more likely had poor glycemic control (AOR=6.45,95%CI=1.967-5.497, P=0.005) than those who had others complication.

Conclusion and Recommendation

Our study investigated the prevalence of poor glycemic control among type 2 diabetic patients was high. About half of the patients were on anti-diabetic medication for between one to four years and slightly above one half of oral hypoglycemic agents were the most prescribed drug regimen. Above half of diabetic patients were had at least one comorbidities and had nephropathy diabetic complication. Hypertension was the most present comorbidities followed by renal disease. Age less than forty years, uneducated patients, glibenclamide and metformin drug regimen, low adherance, cigarette smokers, patients who had comorbidities, and patients who had nephropathic complication of diabetes were significantly factors associated with glycaemic control. Health care workers should have to advice the patients about life style modification and on how they take their medication.

Acknowledgment

We would like to extend our thanks to the data collectors and respondents.

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Editorial Information

Editor-in-Chief

Katsunori Nonogaki
Tohoku University
Japan

Article Type

Research Article

Publication history

Received: June 10, 2021
Accepted: June 20, 2021
Published: June 30, 2021

Copyright

©2021 Gudisa Bereda and Gemechis Bereda. 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.

Citation

Gudisa Bereda (2021) The incidence and predictors of poor glycemic control among adults with type 2 diabetes mellitus in ambulatory clinic of mettu karl referral hospital, southwestern, Ethiopia: a prospective cross sectional study. Diabetes Updates 7: DOI: 10.15761/DU.1000155

Corresponding author

Gudisa Bereda

SWAN diagnostic pharmaceutical importer, Addis Ababa, Ethiopia, Email: gudisabareda95@gmail.com

Table 1. Socio-demographic characteristics of the study of T2DM patients in Mettu Karl Referral Hospital, South-western, Ethiopia, 2021

Variables

Category

Frequency

Percent

Age

≤40 years

56

45.9

>40 years

66

54.1

Sex

Male

67

54.9

Female

55

45.1

Residency

Urban

50

41.0

Rural

72

59.0

Monthly income

≤ 500 ETB

79

64.8

>500 ETB

43

35.2

Marital status

Unmarried

43

35.2

Married

79

64.8

Educational status

Uneducated

45

36.9

Primary

39

32.0

Secondary

27

22.1

Higher education

11

9.0

Social habit

Cigarette smokers

38

31.1

Alcohol drinker

32

26.2

Khat chewing

22

18.0

None

30

24.6

Family history

Yes

45

36.9

No

77

63.1

Magnitude of poor glycemic control

Yes

74

60.7

No

48

393

Table 2. Clinical characteristics and disease related variables among T2DM patients in Mettu Karl Referral Hospital, South-western, Ethiopia, 2021

Variables

Category

Frequency

Percent

Body mass index

<18.5 kg/m2

18

14.8

18.5–24.9 kg/m2

30

24.6

25–29.9 kg/m2

42

34.4

≥30 kg/m2

32

26.2

Fasting blood sugar

≤ 130gm/dl

33

27.0

>130gm/dl

89

73.0

Blood pressure

<140/90 mmHg

78

63.9

≥ 140/90 mmHg

44

36.1

Adherance

Low

56

45.9

Moderate

38

31.1

High

28

23.0

Co-morbidities

Yes

67

54.9

No

55

45.1

Complication

Retinopathy

16

13.1

Cardiac complications

17

13.9

Nephropathy

32

26.2

Neuropathy

12

9.8

None

45

36.9

Type of co-morbidities

Hypertension

55

45.1

DKA

5

4.1

Renal disease

21

17.2

Peripheral neuropathy

29

23.8

Other

12

9.8

Type of treatment

Non-pharmacological

33

27.0

Pharmacological

89

73.0

Table 3. Medication related and life style related characteristics among T2DM patient s in Mettu Karl Referral Hospital, South-western, Ethiopia, 2021

Variables

Category

Frequency

Percent

Duration of treatment

1-4 years

62

50.8

5-10 years

43

35.2

> 10 years

17

13.9

Drug regimen

Oral hypoglycemic agents

87

71.3

Oral hypoglycemic agents+ Insulin

35

28.7

Type of DM drugs

Metformin

41

33.6

Glibenclamide and metformin

19

15.6

Glibenclamide

17

13.9

Metformin and NPH insulin

34

27.9

Metformin+Glibenclamide+ insulin

11

9.0

Numbers of drugs tak en

≤2 drugs

77

63.1

> 2 drugs

45

36.9

Concomitant medicat ion

Yes

50

41.0

No

72

59.0

Type of concomitant medication

Enalapril

21

42.0

Enalapril + ASA

16

32.0

Enalapril + ASA + atenolol

9

18.0

Enalapril+ASA+hydrochlorothiazide

4

8.0

Health diet

Adequate

56

45.9

Inadequate

66

54.1

Physical exercise

Yes

43

35.2

No

79

64.8

Foot care

Yes

27

22.1

No

95

77.9

Self monitoring bloo d glucose

Yes

35

28.7

No

87

71.3

Table 4. Logistic regression analysis of the association between independent variables and poor glycemic control among T2DM patients in Mettu Karl Referral Hospital South-western, Ethiopia, 2021

Variables

Category

n(%)

AOR (95% C.I)

P-value

Age

≤40 years

56(45.9)

2.98(1.089-2.023)

0.034

>40 years

66(54.1)

1

Sex

Male

67(54.9)

1.96(1.043-1.848)

0.078

Female

55(45.1)

1

Educational status

Uneducated

45(36.9)

1.75(1.957-3.649)

0.009

Primary

39(32.0)

1.01(1.968-1.967)

0.869

Secondary

27(22.1)

0.364(0.067-1.028)

0.184

Higher education

11(9.0)

1

Type of DM dr ugs

Metformin

41(33.6.0)

1.873(1.921-2.340)

0.09

Glibenclamide and metformin

19(15.6)

1.043(1.429-3.750)

0.018

Glibenclamide

17(13.9)

0.740(0.694-1.947)

0.873

Metformin and NP H insulin

34(27.9)

1.75(1.967-2.645)

0.095

Metformin+ Insulin + Glibenclamide 

11(9.0)

1

Adherance

Low

56(45.9)

2.68(1.764-4.928)

0.002

Moderate

38(31.1)

1.146(1.437-2.746)

0.645

High

28(23.0)

1

Social habit

Cigarette smokers

38(31.1)

1.978(2.034-3.864)

0.008

Alcohol drinker

32(26.2)

1.34(1.564-2.853)

0.07

Khat chewing

22(18.0)

5.68(2.968-12.476)

0.061

None

30(24.6)

1

Comorbidity

Yes

67(54.9)

2.5(1.967-5.497)

0.028

No

55(45.1)

1

Duration of tre atment

1-4 years

62(50.8)

0.478(0.021-1.017)

0.476

5-10 years

43(35.2)

2.15(1.967-4.231)

0.005

> 10 years

17(13.9)

1

Residency

Urban

50(41.0)

1.254(1.694-2.078)

0.045

Rural

72(59.0)

1

Type of compli cation

Retinopathy

16(13.1)

0.285(0.047-1.074)

0.178

Neuropathy

17(13.9)

1.476(1.967-2.863)

0.710

Nephropathy

32(26.2)

6.45(3.071-17.632)

0.095

Cardiac complicatio ns

12(9.8)

1.435(1.849-2.147)

0.453

None

45(36.9)

1