Non-compliance on DM Treatment Among Diabetic Patients in Arar City, Northern Saudi Arabia

Abdelrahman M.A. Abukanna; Maali S. N. Alanazi; Raghad A. K. Alanazi; Ashwaq A. G. Alanazi; Amaal S. N Alanazi

2020 Volume 10 Issue 5

Non-compliance on DM Treatment Among Diabetic Patients in Arar City, Northern Saudi Arabia

Abdelrahman Mohamed Ahmed Abukanna ¹, Maali Salamah N Alanazi ²*, Raghad Aladham K Alanazi ², Ashwaq Aziz G Alanazi ², Amaal Saeed N Alanazi ²

¹Associate prof. of Internal Medicine, Faculty of Medicine, Northern Border University, Arar, KSA.

²Undergraduate Medical student, Faculty of Medicine, Northern Border University, Arar, KSA.

ABSTRACT

Background: Various methods have been utilized to evaluate and test patient adherence to medications and there is no "gold standard" measure of adherence to medicines. Objectives: To investigate the extent of non-compliance to diabetes treatment and its contributing factors among diabetic patients attending the Diabetes Center at Arar city, Northern Saudi Arabia. Methods: A cross-sectional study was carried out among the target population. Patients already diagnosed to have type 2 DM for at least one-year duration and who were on antidiabetic medication for more than 6 months, aged at least 18 years, attending the diabetic center during the study period, and giving written informed consent to contribute in the study. The collection of data was via personal interviews with diabetic patients. The instrument of data assortment was a structured questionnaire that consists of three sections: section 1 for the Socio-demographic features of the patients as age, sex, marital state, and occupation; section 2 contained questions that assess the adherence patterns by eight-item Morisky Medication Adherence Scale (MMAS-8). Results: According to MMAS scores of DM treatment adherence, the majority (79.8%) of the respondents were poorly adherent, 14.6% were mediumly adherent, and only 5.6% were highly adherent. Significant factors affecting the poor adherence to DM medication were gender, glycosylated hemoglobin level, believing the medication is ineffective, suffering from side effects of the medication, and using alternative medicine (P<0.05). There was a statistically insignificant factor as, educational level, suffering DM complications, period of DM, route of drug administration, receiving DM health education in the last 6 months, understanding the drug regimens, and affordability of the prescribed drugs. Conclusion: In the current study in Arar, Saudi Arabia, the majority of the diabetic patients were poorly adherent to DM treatment.

Key Words: diabetic patients, adherence to DM treatment, MMAS scores of DM treatment adherence, Arar, Saudi Arabia.

INTRODUCTION

WHO describes diabetes mellitus (DM) as a chronic disease, which happens when the pancreas does not secrete sufficient insulin, or when the body cannot use the insulin produced efficiently [1]. This leads to an increased accumulation of glucose in the plasma. [2, 3]

Type 1 diabetes occurs when the pancreas fails to secrete sufficient insulin owing to damage of beta cells, this type was formerly stated as "insulin-dependent diabetes mellitus" (IDDM) or "juvenile diabetes" [4]. Type 2 diabetes instigates with insulin opposition, a disorder in which body cells cannot retort to insulin appropriately [2, 5]. As the disease progresses, a deficiency of insulin could also occur. This type was formerly mentioned to as "non-insulin-dependent diabetes mellitus" (NIDDM) or "adult-onset diabetes", the utmost common reason is a mixture of increased body weight and deficient muscular workout [6].

Gestational diabetes occurs when pregnant women without a previous history of diabetes develop high blood sugar levels [2].

The prevalence of DM is rising speedily internationally and is getting epidemic extents. It is assessed that there are presently 285 million persons with diabetes internationally and this figure is established to rise to 438 billion by 2030 [7].

Adherence to the treatment inflicts significant therapeutic and financial inferences in diabetics. Drug adherence is well-defined as the degree to which the patient administers the medicines approved by his/her physician [8].

Treatment compliance is well-defined as the degree to which an individual's medication use performance agrees with therapeutic advice and persistence as the duration of time from beginning to termination of therapy [9].

Despite the widespread treatment options existing for different phases of type 2 diabetes, researches have shown that fewer than 50% of patients accomplish the glycemic goals suggested by the American Diabetes Association (ADA) and nearly two-thirds die early of cardiovascular illness and complications [10].

Even though figures reported by a study in the USA showed a rise in the number of cases with identified diabetes who accomplished glycemic, cardiovascular and fat regulation from 7.0% to 12.2% throughout the period of 1999 to 2006, and adherence was quite low, with a significant level of improvement [11].

Non- adherence may be primary non-adherence or non-compliance during treatment. Primary non- adherence refers to those patients who receive prescription but fail to obtain medications from the beginning, its incidence has been reported to be 31% [12].

A WHO report has shown that in developed countries, the rate of non-compliance in patients with chronic diseases like DM is about 50% and it could be even higher in developing countries [13].

Various factors influence non-compliance which may be patient-centered, therapy-related, health care system-related, societal, and financial issues or disease factors [14].

Patient-centered factors include sociodemographic factors (age, sex, and level of learning), psychosomatic factors comprising incentive to treatment compelling, patient-physician rapport, and patient information [15]. Therapy-related influences include route, form, and period of usage, difficulty of treatment particularly as patients may be on many prescriptions, price of prescription particularly if co-payment is an issue, and adverse effects. Healthcare system factors include presence and ease of access to health care, and the health provider-patient interactions [16].

Guidelines from the ADA and the European Association for the Study of Diabetes (EASD) stress the importance of diet and exercise in the treatment of all phases of type 2 diabetes [17].

However, with reverence to muscular exercise, diabetes counselors take into consideration that, lack of interest as well as somatic diseases to be the main obstacles to adherence, although patients stated obstacles to adherence are mostly related to convenience, comprising factors such as the climate; however, only near a quarter of the patients stated that they follow exercise plan [18].

Objective

The study aimed to investigate the extent of non-compliance to diabetes treatment and its precipitating factors among diabetic patients attending the Diabetes Center at Arar city, Northern area of Saudi Arabia.

METHODOLOGY

Studied population & locality

Patients already diagnosed to have type 2 DM for at least one year of duration and on treatment for at least 6 months, attending diabetes center at Arar city, Northern area of Saudi Arabia, were included in the study.

Study design

A descriptive cross-sectional study was conducted on the target population.

Inclusion criteria

The study included patients who were on antidiabetic medication for more than 6 months, aged at least 18 years, attending the diabetic center during the study period, and consented to be included in the study.

The study was conducted throughout the period from May 1, 2020 to August 31, 2020.

Exclusion criteria: Patients recently identified with diabetes (fewer than 6 months), age of less than 18 years, and unconscious and very ill patients.

Sample size

According to the equation: N=z² p (1- p) / d².
Where n=the desired sample size
Z=the standard normal deviation (1.96).
P= the prevalence of the problem.
d =the degree of accuracy required (0.05).

Throughout the period from 1^st of May, 2020 till the end of August, 2020. In our study, the desired sample was 400 patients.

Sampling Technique

The cases were selected using a systematic random sampling technique. First, one case was chosen randomly from the attendees of the center. Second, every 2^nd case will be included until the end of the sample (400 cases).

Study tool

The collection of data was via personal interviews with diabetic patients. The instrument of data assortment was a structured questionnaire that consisted of three sections: section 1 for the Socio-demographic features of the patients as age, sex, marital state, and occupation; section 2 contained questions that assess the adherence patterns by eight-item Morisky Medication Adherence Scale (MMAS-8) [19]. A score of 8 indicates high adherence, a score of 6-7 indicates medium adherence, while a score of less than 6 indicates poor adherence, and section 3 included health education attendance, route of medication administration, patients self-rating of the extent of understanding of their medication regimens, antagonistic drug reactions, patients' ability to afford the recommended medicines, period of diabetes, and usage of alternative drugs.

Ethical considerations

Agreement to conduct the study was attained from the Research Ethics Committee of the Northern Border University. Data was anonymous for patient confidentiality and the questionnaires were kept safely.

Data management and Statistical analysis

The collected data was entered and analyzed using the Statistical Package for the Social Science (SPSS Inc. Chicago, IL, USA) version 23. Descriptive statistics will be performed. Percentages were given for qualitative variables. The determining factors were measured by means of the Chi-square test. P-value was considered significant if P <0.05.

RESULTS

Table 1: Shows the socio-demographic features of the participants. 59.5% of the respondents were females, 42.4% were between 19 to 40 years old. Only 15.3% were elderly. 40.8% had a normal BMI. More than half (62.3%) of the respondents were married. Most of the respondents lived in urban areas (90.7%), and 53.0% had a university degree. 73.8% were nonsmokers. Regarding DM complications, 19.3% suffered from heart disease, and 12.1% reported eye complications.

Table 2: Shows MMAS scores and factors affecting DM adherence in the respondents. According to MMAS scores of DM treatment adherence, the majority (79.8%) of the respondents were poorly adherent, 14.6% were mediumly adherent and only 5.6% were highly adherent. The period of DM was between 2 and 10 years in more than half (53.3%) of the respondents. Glycosylated hemoglobin was good (less than 7%) in 57.9% of the respondents. Half of the respondents were previously admitted to the hospital due to DM cause. 68.8% only received one health education or none about DM in the last 6 months. 27.4% suffered from untoward effects of the medication, 44.9% thought it is unaffordable, and 18.7% believed it is ineffective.

According to MMAS scores of DM treatment adherence, the majority (79.8%) of the respondents were poorly adherent, 14.6% were mediumly adherent, and only 5.6% were highly adherent. Table 3 illustrates the relation between poor adherence to DM medication and factors affecting it. There was a statistically significant relation with gender, glycosylated hemoglobin, admission to the hospital because of DM cause, believing that medication is ineffective, suffering from untoward effects of the medication, and using alternative medicines. There was a statistically insignificant relation with the academic level, suffering DM complications, period of DM, route of drug administration, receiving DM health education in the last 6 months, understanding the drug regimens, and affordability of the prescribed drugs.

Table 1. Socio-demographic characteristics of the participants, 2020 (N=321).

Variables	Frequency (N=321)	Percent (%)
Sex
Male	130	40.5
Female	191	59.5
Age group
18 years or younger	21	6.5
19 – 40 years	136	42.4
41 – 60 years	115	35.8
61 years or older	49	15.3
BMI group
Low	11	3.4
Normal	131	40.8
Overweight	81	25.2
Obese	98	30.5
Marital status
Single	83	25.9
Married	200	62.3
Divorced	11	3.4
Widowed	27	8.4
Residence
Urban area	291	90.7
Rural area	30	9.3
Educational level
Introductory	37	11.5
Secondary	76	23.7
University degree	170	53.0
Illiterate	38	11.8
Employment
Employed	140	43.6
Non-employed	117	36.4
Student	64	19.9
Residence
Urban area	291	90.7
Rural area	30	9.3
Smoking status
Smoker	75	23.4
Heavy smoker (25 cigarettes or more daily)	9	2.8
Non-smoker	237	73.8
Alcoholism
Yes	10	3.1
No	311	96.9
Complications
Heart disease	62	19.3
Eye complications	39	12.1
Renal disease	11	3.4
Limb paralysis	5	1.6
Others	19	5.9

Table 2. MMAS score and factors affecting DM adherence in the participants, 2020. (N=321)

Variables	Frequency (N=321)	Percent (%)
MMAS score
High adherence	18	5.6
Medium adherence	47	14.6
Poor adherence	256	79.8
Period of DM
Less than 2 years	90	28.0
2 – 10 years	171	53.3
More than 10 years	60	18.7
Glycosylated hemoglobin
Good (less than 7%)	186	57.9
Bad (higher than 7%)	135	42.1
Blood glucose monitoring at home
Yes	270	84.1
No	51	15.9
Route of drug administration
Oral pills	160	49.8
Injection	139	43.3
Both	22	6.9
Admission to the hospital because of DM
Yes	162	50.5
No	159	49.5
Health educations about DM in the last 6 months
Two or more	100	31.2
1 or less	221	68.8
Understanding the drug regimens
Yes	273	85.0
No	48	15.0
Believing the medication is ineffective
Yes	60	18.7
No	261	81.3
Suffering from side effects of the medication
Yes	88	27.4
No	233	72.6
Affordability of the prescribed drugs
Yes	177	55.1
No	144	44.9
Using alternative medicine
Yes	101	31.5
No	220	68.5

Table 3. Relation between poor adherence to DM medication and factors affecting it.

		Adherence		Total (N=321)	P-value
		Poor (N=256)	High or medium (N=65)	Total (N=321)	P-value
Gender	Male	97	33	130	0.041
	Male	37.9%	50.8%	40.5%
	Female	159	32	191
	Female	62.1%	49.2%	59.5%
Academic level	Introductory	31	6	37	0.774
	Introductory	12.1%	9.2%	11.5%
	Secondary	60	16	76
	Secondary	23.4%	24.6%	23.7%
	University degree	133	37	170
	University degree	52.0%	56.9%	53.0%
	Illiterate	32	6	38
	Illiterate	12.5%	9.2%	11.8%
Glycosylated hemoglobin	Good (less than 7%)	158	28	186	0.005
	Good (less than 7%)	61.7%	43.1%	57.9%
	Bad (higher than 7%)	98	37	135
	Bad (higher than 7%)	38.3%	56.9%	42.1%
Suffering from DM complications	Yes	110	26	136	0.387
	Yes	43.0%	40.0%	42.4%
	No	146	39	185
	No	57.0%	60.0%	57.6%
Period of DM	Less than 2 years	73	17	90	0.609
	Less than 2 years	28.5%	26.2%	28.0%
	2 – 10 years	133	38	171
	2 – 10 years	52.0%	58.5%	53.3%
	More than 10 years	50	10	60
	More than 10 years	19.5%	15.4%	18.7%
Route of drug administration	Oral pills	125	35	160	0.769
	Oral pills	48.8%	53.8%	49.8%
	Injection	113	26	139
	Injection	44.1%	40.0%	43.3%
	Both	18	4	22
	Both	7.0%	6.2%	6.9%
Admission to the hospital because of DM	Yes	121	41	162	0.016
	Yes	47.3%	63.1%	50.5%
	No	135	24	159
	No	52.7%	36.9%	49.5%
Receiving DM health education in the last 6 months	Yes	82	18	100	0.303
	Yes	32.0%	27.7%	31.2%
	No	174	47	221
	No	68.0%	72.3%	68.8%
Understanding the drug regimens	Yes	221	52	273	0.140
	Yes	86.3%	80.0%	85.0%
	No	35	13	48
	No	13.7%	20.0%	15.0%
Believing the medication is ineffective	Yes	38	22	60	0.001
	Yes	14.8%	33.8%	18.7%
	No	218	43	261
	No	85.2%	66.2%	81.3%
Suffering from side effects of the medication	Yes	61	27	88	0.004
	Yes	23.8%	41.5%	27.4%
	No	195	38	233
	No	76.2%	58.5%	72.6%
Affordability of the prescribed drugs	Yes	140	37	177	0.428
	Yes	54.7%	56.9%	55.1%
	No	116	28	144
	No	45.3%	43.1%	44.9%
Using alternative medicine	Yes	73	28	101	0.019
	Yes	28.5%	43.1%	31.5%
	No	183	37	220
	No	71.5%	56.9%	68.5%

DISCUSSION

Several variables influence glycemic regulation in patients with diabetes, who are proven to increase adherence to DM drugs, and medication effectiveness is reduced by lack of adherence [20]. Various methods have been used to evaluate and test patient adherence to medications and there is no "gold standard" measure of adherence to medicines. Morisky et al. recently created an 8-item self-reported scale called the Morisky Medication Adherence Scale (MMAS) [21].

Our study was conducted to investigate the extent of non-compliance to diabetes treatment and its precipitating factors among diabetic patients attending the diabetes center at Arar city, Northern area of Saudi Arabia. We found that 5.6% of our participants scored high adherence (n= 18), 14.6% scored medium adherence (n= 47) and 79.8% scored poor adherence (n= 256). A similar study in the KSA found high (MMAS = 8) levels of OHA adherence in 40% (n = 158), moderate (6≤ MMAS <8) levels in 37% (n = 145) and low (MMAS <6) adherence in 23% (n = 92) [22]. Another study reported that (58%) were reflected highly adherent (MMAS = 0), (39.5%) were medially adherent (MMAS = 1–2), and nine (2.5%) had low adherence (MMAS ≥ 3) [23]. According to the findings of Elsous et al., it was revealed that 279 (84.5%) were adherent while 51 (15.5%) were non-adherent [24].

Another study reported that the percentages of cases with low, medium, and high adherence to their prescribed medicines were 24.9 %, 37.9 %, and 37.2 %, respectively [25]. This was on the line with results of another study reported that 64.6 % of the studied cases were found not adherent (MMAS-8© adherence score < 6), 26.5 % and 9.0 % had low adherence (MMAS-8© adherence score < 6) and medium adherence (MMAS-8© adherence scores of 6 to 7) to the prescribed drugs, respectively [26]. This agreed with the results of a previously reported study that the percentage of cases that lowly adherent to their medicine (MMAS-8 ≤ 6) was 32.2% [27]. Another Malaysian study reported the mean ± SD of MMAS scores was 6.13 ± 1.72 [28].

Educational websites have been set up to increase health awareness in which patients may discuss any concerns that may prevent adherence to medications.

According to our results, we found a statistically significant relation between gender and medication adherence (males had higher adherence). The level of education was not associated with medication adherence. A previous study revealed that younger age and lower education were the two independent factors that were significantly related to non-adherence to medication. The same study reported that gender, education, marital status, income, BMI, diabetes duration, completion of the diabetes education program, and enrollment in the home blood glucose monitoring were not statistically significant predictors of medication adherence [22].

In another study, the participants aged ≥70 years were 79% more adherent than those below 50 years (P= 0.016). Respondents who graduated from senior high schools were 3.7 times less adherent to their medications than those who graduated from tertiary schools [24]. This agreed with the study results reported that respondents having low adherence to their medicines, 55.8 % had a lower degree of knowledge about diabetes, 63.6 % had deprived self-care activities and 16.9 % had a lower level of glycemic control [25]. In a cohort of patients, the strongest independent predictor of adherence was the patient’s education level [26]. In another study, the MMAS‐8 score had a negative weak correlation with the level of HbA1c [27].

According to our study results, unlike expected, good glycemic control was associated with poor medication adherence (less than 7%) and bad (higher than 7%) was associated with high medication control. This may be explained by the severity of diabetes in poorly adherent patients was less than in high adherence patients.

Unlike our results, many previous studies reported that the enhancement and improvement of patients’ adherence may lead to the improvement of their diabetes control. Another study reported that in cases with a medium degree of adherence to drugs, 17.9 % were found to have medium degree of knowledge on diabetes, 41.9 % had poor self-care performances and in 21.4 % the glycemic control was bad and those respondents who had a high level of adherence to medications, 35.7 % had a high level of diabetes knowledge, 53.9 % had sufficient self-care performances, and 54.8 % of the glycemic control was good [25]. Al Mazroui reported a significant decrease in HbA1c level among diabetics getting a rigorous health educational program along a period of 12 months, of HbA1c 8.5 % (8.3, 8.7) vs. 6.9 % (6.7, 7.1) [29]. Reed showed the essential role of chronic diabetes clinics in the UAE in optimizing diabetes outcomes as measured by HbA1c levels and blood pressure. However, none of the earlier 'UAE-based' research was intended to research opioid adherence standards among diabetics [30].

In another local hospital-based sample of diabetes patients participating in a pharmacist-controlled treatment program, the median compliance rate and the average glycemic control were 41.3% and 7.4%, respectively. [31].

In another research, glycemic regulation represented by HbA1c was shown to be substantially linked to MMAS scores in which lower HbA1c (better glycemic regulation) was correlated with higher adherence scores in the sample group. A strong correlation was found between the 8-item MMAS scores and the diabetic regulation represented by HbA1c, with a sensitivity and specificity of 77.6% and 45.3%, respectively [28]. Schectman et al. found that for each 10% increment in medication adherence HbA1c level decreased by 0.16% [32]. Ho et al. found that every 25% increase in adherence to oral hypoglycemic was associated with a −0.05% reduction in HbA1C [33]. In another study, it was found that higher non-adherence of drugs was associated with poorer glycemic control. Patients with PDC of <40% had a 0.38 (about 5%) increase in HbA1c while those with PDC of >40% had no significant change in HbA1c [34].

CONCLUSION AND RECOMMENDATIONS

In the present study in Arar, Saudi Arabia, the majority of the diabetic patients were poorly adherent to DM treatment. The study also revealed that health education for diabetic patients is necessary to guard against non-adherence and prompt management should be provided to patients with glycosylated hemoglobin levels. Large-scale national researches are needed to include all diabetic patients in Saudi Arabia.

Conflict of interest: The authors declare that there is no conflict of interest.

Budget: No funding institutions, this study is self-funded.

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