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Diabetes related distress is a major challenge in patients with diabetes mellitus.
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Over one third of patients with DM have diabetes related distress.
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Patients with type 1 DM had a higher rate of diabetes related distress and showed higher level of stress in all DRD domains.
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Diabetes related distress and low adherence to treatment rates are negatively correlated with glycosylated hemoglobin.
Abstract
Aims
Diabetes related distress (DRD) is a negative emotional reaction to stresses associated with diabetes mellitus (DM) and its management. This study estimated the burden of DRD and self-reported adherence to treatment (SRAT) among patients with DM and investigated their relationship with glycemic control.
Methods
A cross sectional study of consented 157 diabetics was conducted using the17-item Diabetes Distress Scale (DDS). It measures distress at four subscales: Emotional Burden (EB), Physician-related (PD), Regimen-related (RD) and Interpersonal Distress (ID). SRAT was assessed using Morisky’s scale. Glycemic control was assessed using the most recent HbA1c results. Multivariable linear regression analysis was used for adjustment of confounders and bootstrap Confidence Interval was used to test for the occurrence of mediating effect.
Results
Average age was 44.5 ± 16.0 years, 65% were females, 79% had type 2 DM and nearly 55% has had DM for more than 7 years and the average HbA1c was 8.9 ± 2.2%. Clinically significant DRD was reported by 37% of the participants, EB and RD in 40.8%, PD in 46.5%, and ID among 32.5%. Younger patients showed higher level of stress compared to older participants and patients with type 1 DM showed higher level of stress in all DRD domains. Only 46% of patients were defined as having satisfactory SRAT and improvement of SRAT significantly enhanced the glycemic control (r = −0.32, p < 0.01). DRD and low SRAT negatively correlated with HbA1c; increasing the DRD by one point may increase the HbA1c on average by 0.41 (C.I. 0.02–0.80) and will indirectly raise the HbA1c by 0.24 (C.I. 0.04–0.47) through the mediating effect of low SRAT.
Conclusion
DRD and low SRAT are commonly reported among DM patients and both are indirectly correlated. The mediating effect of low SRAT highlights the clinical role of DRD and clarifies the process by which distress affect the outcome of DM management.
Diabetes Mellites (DM) is one of the most common chronic disease in the world and living with DM requires comprehensive management such as medical treatment, diet control and lifestyle modification to achieve an acceptable level of glycemic control and hence, avoid short- and long term-complications [
]. The prevalence of DM is progressively increasing globally. The World Health Organization (WHO) and the International Diabetes Federation reported that in 2019, approximately 54.8 million adults aged 20–79 years, or 12.8% of the regional population in the Middle East and North Africa have DM – with another alarming figure indicating that up to 1 out of 4 Saudis has DM [
Living with DM is considered stressful as patients need to follow a special lifestyle in their daily diet, physical activity, drug adherence and blood sugar monitoring [
]. Achieving an acceptable level of glycemic control does not depend merely on the clinical management of DM but it is rather influenced by the degree of stress that patients with DM face [
Diabetes-related distress (DRD) is commonly referred to as patient’s concerns about the burden of DM and its complications, perception of support, emotional burden and in accessing proper medical care and advice [
]. The Diabetes-Distress scale (DDS) is one of the most validated instruments used in assessing DDS and the four distress-related domains: “emotional burden (EB), physician-related distress (PD), regimen related (RD) distress subscale and diabetes related interpersonal distress (ID)” [
]. The DDS is a 17-items questionnaire which measures different aspects of DM-specific distress to support the clinician and patients in recognizing where interventions might be helpful [
]. Unfortunately, the average adherence to long-term therapy for chronic diseases does not exceed 50% in developed countries, moreover, the adherence to lifestyle modification and proper diet is much lower than adherence to treatment [
]. This poor adherence is reflected clearly on the DM control as measured by glycosylated hemoglobin (HbA1c) which reflects not only the current glycemic status but also predicts its short- and long-term complications [
Understanding the relation between DRD, adherence to treatment and glycemic control can help clinicians in providing comprehensive care to their patients rather than depending on the HbA1c alone as an indicator for DM control. However, studies that attempts to clarify the mechanism through which DRD can influence glycemic control of DM patients are limited and poorly understood. Several descriptive studies have demonstrated that high DRD is associated with poor glycemic control and poor behavioral self-management skills like eating unhealthy diet, physical inactivity, and poor medication adherence [
Diabetes Distress and Care Registry at Tenri Study Group
Diabetes distress, but not depressive symptoms, is associated with glycaemic control among Japanese patients with type 2 diabetes: Diabetes Distress and Care Registry at Tenri (DDCRT 1).
Physical activity advice only or structured exercise training and association with HbA1c levels in type 2 diabetes: a systematic review and meta-analysis.
]. Thus, how these factors interact or are linked in the causal pathway remain unclear. For example, it has been argued that the occurrence of DRD may lead to poor behavioral self-management of DM leading to poor glycemic control [
]. Moreover, others researchers argue that patients with DM who had poor glycemic control may develop low motivation for undertaking lifestyle changes like healthy diet, exercise etc, which in turn may lead to high DRD. Some previous studies suggest that these constructs may interact in a bidirectional manner over time [
]. However, a randomized controlled trial exploring the relationship between DRD, self-management and glycemic control concluded that the interrelationships between these constructs are complex and are likely to follow multifaceted pathways [
Prevalence and predictors of depression, anxiety, and stress symptoms among patients with type II diabetes attending primary healthcare centers in the western region of Saudi Arabia: a cross-sectional study.
Depression and anxiety among hypertensive and diabetic primary health care patients. Could patients’ perception of their diseases control be used as a screening tool?.
]. Nevertheless, there are no studies that assessed the relation between DRD, adherence to treatment and HbA1c among patients with type 1 and type 2 DM. In this study, we aimed to explore DRD and adherence to treatment among patients with DM and to investigate their relationship with glycemic control.
2. Material and methods
2.1 Study design and subjects
This study is a cross-sectional study of a purposive sample of 157 patients with DM recruited in waiting areas at a tertiary hospital in Riyadh, KSA. The data was collected from the outpatient ward of the hospital. Patients with DM who were attending the outpatient services department and who were clinically diagnosed as diabetic patients were invited to participate in the study.
2.2 Inclusion criteria
Eligible patients of the study were adults at least 18 years of age and less than 99 years old; outpatients who had a confirmed diagnosis of DM for at least one year, and were attending follow up clinic for DM regularly.
2.3 Exclusion criteria
The patients who were excluded from the study are those who were not able to complete the survey because they had severe illness or complications from their DM, and patients who were having difficulty in understanding the questions being posed by the survey.
2.4 Sampling procedure and sample size
The study utilized purposive sampling. Therefore, all eligible patients attending the outpatient DM clinic from December 2020 to March 2021 were invited to participate in the survey. Therefore, all eligible consecutive consenting patients with DM during the study period completed the survey in a private room in the clinic.
Sample size calculation was based on data derived from previous literature showing that the correlation between depressive mood and adherence to treatment is intermediate (r = 0.15–0.25) [
]. Using G-Power program for calculating the minimal sample size, with 95% level of significance (α = 0.05) and a power of 80% (β = 0.2), the minimal sample size needed was 89. We recruited 157 patients with DM to compensate for the missing data in HbA1c readings.
2.5 Data collection tool
Data collection tool was a validated pre-tested questionnaire. This questionnaire was composed of different sections assessing various domains.
1
Sociodemographic data: This included age, sex, marital status and average monthly income of the family.
2
Second section was about the medical history of the DM and presence or absence of comorbidities; duration and type of DM, type and frequency of medication, family history of DM, other comorbid conditions and history of DM complications.
3
The third section included DDS composed of 17 questions that evaluated diabetes related problems over the last one month [
]. The DDS-17 has four distinct subclasses of diabetes-related distress i.e., EB (5 items), PD (4 items), RD (5 items), and ID (3 items). The responses to each item in the questionnaire were rated on a 6-point Likert scale as follows (1, not a problem; 2, a slight problem; 3, a moderate problem; 4, somewhat serious problem; 5, a serious problem; and 6, a very serious problem). The cutoffs for low, moderate, and high distress was a mean score of: <2, between 2–2.9, and high distress: ≥3 respectively [
]. The DDS-17 was translated from English to Arabic, both forward and backward translations were carried out. Its reliability was tested using Cronbach’s Alpha and was excellent (Cronbach’s Alpha = 0.91). In this study, patients were considered to have no clinically relevant DRD if their scores were less than 2.9, if they scored 3 or more, they were considered as having clinically significant distress level.
4
Self-reported adherence to treatment (SRAT) was measured using Morisky Medication Adherence Scale (MMS-8): this is a validated tool for evaluation of SRAT [
]. The tool consists of eight questions. The response options are “yes” or “no” for items 1 through 7 and item 8 has a five-point Likert response scale. Each “no” response is rated as 1 and each “yes” response is rated as 0 except for item 5, in which each “yes” response is rated as 1 and each “no” response is rated as 0. For Item 8, the code (0–4) has to be standardized by dividing the result by 4 to calculate a summated score. Total scores on the MMAS-8 range from 0 to 8, with scores of 8 reflecting high adherence, 7 or 6 reflecting medium adherence, and <6 reflecting low adherence. Permission to use the scale was granted by Donald Morisky, the copyright holder of the instrument. Also, after translation and piloting, its reliability was tested by Cronbach’s Alpha which was very good and was excellent (Cronbach’s Alpha = 0.69).
5
Lastly, we reviewed laboratory work-up of each patient to assess the most recent HbA1c (maximally within the last 3 months before the survey) of each patient. Overall, 77 of the patients did not have a recent HbA1c.
2.6 Statistical analysis
Descriptive statistics in terms of means, standard deviations were used to describe the studied sample. Analysis of quantitative data by t-test and association of categorical variables by chi-square test were conducted. Pearson’s correlation coefficient was used to test correlations between quantitative variables.
The normality of DRD and HbA1c scores was assessed using a visual inspection of graphs. These were found to be normally distributed. Group means were evaluated using the analysis of variance (t-test where appropriate). Multivariable linear regression analysis was performed with DRD scores as the outcome variable and HbA1c and SRAT as predictor variables. Variables with clinical importance (age and sex) and those with univariate p < 0.3 were included as the explanatory variables using the Enter method. Multicollinearity was assessed using the variance inflation factor. Statistical mediation effect was assessed using structural equation modelling using the PROCESS macro for SPSS [
]. The model was adopted considering HbA1c as an outcome, DRD as a predictor and SRAT as a mediator. We hypothesized that the effect of DRD upon HbA1c can be explained partially by the SRAT. The effect of DRD on HbA1c was measured by total effect (sum of direct and indirect effect of DRD on HbA1c), and the mediating effect was measured by the indirect effect of DRD on HbA1c via SRAT. Statistical significance of mediating effect was tested using percentile bootstrap Confidence Interval (C.I.) approach where 5000 samples were randomly generated from the data set to create the CI. P-value less than 0.05 was considered statistically significant.
3. Results
A total of 166 patients were invited to participate in the survey and 157 of them completed the survey, giving a response rate of (94.6%). Table 1 shows the characteristics of the studied sample. The participants have an average age of 44.4 ± 15.9 years with the majority 103 (65.6%) aged between 30 and 60 years. There was a predominance of females 103 (65.6%) and Saudi patients 141(89.8%). Only 10 (6.4%) of the patients were illiterate whilst more than 33% of them had university or higher education. The patients were asked their perception regarding their household income meeting their needs, about 70% of the participants believed that their income was enough or even more than enough because they have some savings.
Seventy-nine percent of the patients had type 2 DM, and the patients have had their DM illness for an average of 9.3 ± 7.8 years and receiving on average 1.9 ± 1.1 antidiabetic medications per day. The mean fasting blood sugar of the patients was 172 ± 83.5 mg/dl and their average HbA1c was 8.9 ± 2.3. Only 15 (18.8%) of the participants were controlled as defined by having HbA1c less than 7% while 28.7% reported no diabetic complications.
Clinically significant DRD was reported by 60 (38.2%) of the participants. EB and RD were each reported by 64 (40.8%) of the patients, PD by 73 (46.5%), and ID among 51 (32.5%). About 45% of the patients were defined as having satisfactory SRAT.
Table 2 shows relation between DRD and its domain with various characteristics of the participants. Younger patients steadily show higher level of stress compared to older participants and this trend reached statistical significance in RR (p < 0.05). Patients with type I DM showed higher levels of stress in all DRD domains and they significantly suffered from RR more than those with type 2 DM (60.6 versus 35.5%, p < 0.05). DRD and its domains were noticed more seriously among patients who suffer from more complications especially in ED, PR and DRD. Additionally, poor level of SRAT was significantly associated with higher level of stress particularly RR and ID. DRD and all its domains were insignificantly associated with gender, economic level, marital status, education, type or duration of diabetes (p > 0.05). Moreover, patients who suffer from one sub-type of distress are significantly more likely to endure other distresses.
Table 2Relation between diabetes related distress and patients’ characteristics.
p – value based on Chi-square test. EB: Emotional Burden, PR: Physician Related Distress, RR: Regimen Related Distress, ID: Interpersonal Distress, DRD: Diabetes Related Distress, HbA1c: glycosylated haemoglobin.
Table 3 displays the relation between SRAT and different domains of DRD. Patients suffering from any DRD significantly reported less adherence to treatment scores. Meanwhile, indirect correlation between SRAT and all domains of DRD was prominent as reported by the negative Pearson’s correlation coefficients and the significant P-value. The negative correlation was also confirmed between the HbA1c level and the SRAT; the better adherence score, the lower level of HbA1c (r = −0.32, p = 0.003).
Table 3Relation between Self-Reported Adherence to Treatment and Diabetes Related Distress.
Adherence to treatment mean ± SD
p-value
Pearson’s Correlation coefficient
p-value
EB
0.002
−0.32
<0.001
Yes
4.4 ± 2.2
No
5.1 ± 1.8
PR
0.123
−0.30
<0.001
Yes
4.8 ± 2.2
No
4.5 ± 1.9
RR
<0.001
−0.41
<0.001
Yes
4.0 ± 2.1
No
5.8 ± 1.7
ID
<0.001
−0.33
<0.001
Yes
4.2 ± 2.0
No
5.5 ± 1.9
DRD
0.001
−0.38
<0.001
Yes
4.3 ± 2.3
No
5.5 ± 1.8
HbA1c
0.032
−0.32
0.003
Controlled (<7)
5.9 ± 1.6
Uncontrolled 7+
4.5 ± 2.2
Emotional Burden, PR: Physician Related Distress, RR: Regimen Related Distress, ID: Interpersonal Distress, DRD: Diabetes Related Distress, HbA1c: glycosylated haemoglobin.
In univariate analysis (Table 4), patients who had poor adherence rate had a significantly higher DRD score (3.02), compared to those with good (2.44) and very good (2.04) adherence rates (p = 0.001). Also, higher levels of HbA1c level was significantly related to the higher DRD scores (p = 0.04). Patients who are below 30 years old had higher DRD scores compared to older individuals, but the difference was not statistically significant (p = 0.09). Similarly, patients who had one or more DM complications had higher DRD scores compared to those without any complications, but the difference was also not statistically significant (p = 0.08). In multivariable linear regression analysis (Table 5), having one or more complications significantly predicted higher DRD scores (p = 0.01), while very good adherence rates were inversely related to higher DRD scores (p = 0.002).
Table 4Univariate analysis of factors associated with higher DRD score.
Fig. 1 shows the mediating effect of SRAT on the relation between DRD and HbA1c. The total effect of DRD on HbA1c was 0.41 (C.I. is 0.02 to 0.80) meaning that increasing the DRD by one point can increase the HbA1c on average by 0.41%. Additionally, there was a significant indirect effect of DRD on the HbA1c level through SRAT, (0.24, C.I. = 0.04–0.47) indicating that increasing the DRD by one point will increase the HbA1c by 0.24% through the mediating effect of SRAT (Table 6).
Fig. 1Mediating effect of Self-reported Adherence to treatment (SRAT) in the relation between Diabetes Related Distress (DRD) and HbA1c.
The current study revealed that a considerable proportion of a sample of Saudi patients with DM are suffering from clinically significant DRD and poor SRAT. Both parameters were positively associated with advancement of age. No other sociodemographic factors or diabetes-related attributes were significantly associated with DRD or SRAT except the number of diabetes complications. DRD and SRAT negatively correlated with HbA1c; increasing the DRD by one point may directly increase the HbA1c on average by 0.17 and will indirectly raise the HbA1c by 0.24 through the mediating effect of SRAT.
The prevalence of clinically significant DRD among our patients was 38.2% which was higher than the findings of a similar local study that showed 25% prevalence of moderate to high DRD [
]. The difference in the reported figures can be explained by the differences in demography of the studied samples, type of DM and frequency of associated complications.
In our study, younger age was significantly associated with DRD. This is comparable to other studies that demonstrated a significant correlation between DRD with age [
]. Older age patients showed less level of distress that can be predicted as they already suffer from other comorbidities, nevertheless, younger patients are not used to being sick or experienced in the management of chronic diseases compared to their peers. Living with DM requires the patient to be committed to many daily regimens that are not expected to be easily tolerated by younger adults as reflected by the prominent differences in RR domain.
Patients with diabetic complications were found to have more clinically significant DRD, mainly ED and PR domains. These findings are expected due to the high burden of diabetic complication with possible frequent hospital visits and admissions. The significant association between DRD and diabetic complications was also reported in other researches [
Gender, economic level, marital status, level of education and duration of DM were all found to be insignificant factors in relation to DRD. The relation between DRD and these factors revealed inconsistent findings in previous studies [
Depression and anxiety among hypertensive and diabetic primary health care patients. Could patients’ perception of their diseases control be used as a screening tool?.
]. Overall, in studies among rural African American women and Asian patients, there was an insignificant association between their demographic characteristics and DRD [
]. In contrast, there are other studies who found a significant relationship between the DDS score and low income, unemployment, gender with higher rates among females [
DRD prevalence was studied mainly among patients with Type 2 DM as it was believed that distresses faced by both groups are substantially different. In this study, we have assessed DRD prevalence in type 1 DM and type 2 DM patients. We found that DRD prevalence was 36.3% among patients with type 2 DM and 45.5% in type 1 DM. It comes as no surprise, given that living with type 1 DM requires adherence to daily doses of insulin adjusted all the time according to glucose level along with frequent glucose monitoring furthermore the younger age of type 1 DM patients can add to their distress.
Relation between DRD and glycemic control have been reported inconsistently by various studies [
], conducted among 700 Asian patients with type 2 DM, the prevalence of DRD was 49.2% and no significant relation was detected between DRD and HBA1c. Gonzalez et al., in 2016 showed that 46.2% of type 2 DM patients had clinically significant diabetes distress and defined negative correlation between emotional distress and HbA1c [
In the current study, poor SRAT Was reported by nearly 55% of the participants while 36.4% of them had good SRAT and only 8.9% showed very good level of SRAT. These findings are higher than other national reports; good adherence was reported by Saudi researchers to range from 23% to 35% [
]. These figures are suboptimal when compared to the target of good adherence of DM patients to be around 80% in order to assure an adequate level of glycemic control [
]. The differences in the reported level of adherence to treatment is variable probably because different tools were used to measure adherence to treatment.
Participants reporting higher level of DRD had the lowest SRAT and, correspondingly, demonstrated higher HbA1c values. These results agree with those revealed by many researchers who also demonstrated a significant relationship between DRD and adherence to medications [
Diabetes distress but not clinical depression or depressive symptoms is associated with glycemic control in both cross-sectional and longitudinal analyses.
Reaching a satisfactory level of HbA1c is assumed to be achieved by proper adherence to treatment and many studies demonstrated the relation between adherence to diabetes treatment and good glycemic control. However, many psychological factors are considered to affect the adherence to treatment such as depressive disorders, DRD, self-efficacy, emotional distress, and many other concerns [
]. The present study adds to the current body of evidence for this strong relation between adherence to treatment, glycemic control and various DRD domains.
This study clarified the interaction between DRD, SRAT and glycemic control where SRAT was a mediating factor explaining the negative effect of DRD on HbA1c. Patients who were overwhelmed by their distress may simply stop medications and their glycemic control may worsen [
]. In addition, patients may intentionally stop taking their medication if they have concerns about the efficacy or side effects of the drugs while they may comply with their medication if they receive proper and clear encouraging instructions from their physicians [
“I did not want to take that medicine”: African-Americans’ reasons for diabetes medication nonadherence and perceived solutions for enhancing adherence.
Although logically and clinically accepted, uncontrolled HbA1c is mostly treated by intensifying medications, the situation may be completely different among distressed patients. The inhibitory effect of DRD on the medication adherence can mask the expected beneficial effect of more medications and tighter control of diabetes. These findings signify the importance of managing DRD to consequently improve the adherence to treatment that can results in better control of diabetes. Many studies tested various interventions to alleviate the DRD and their findings are encouraging as DRD appeared very responsive to various interventions among different patients with DM [
Although there were several strengths in the present study, it has some limitations. One of the limitations is the cross-sectional nature of the study design; therefore, the potential for causality in the relationships between DRD, SRAT and HbA1c cannot be determined. Second, purposive sampling was used to recruit the study participants from a single tertiary heath facility. Therefore, the findings of the study may not be generalizable to the whole country. Third, adherence rates were assessed using self report by the patients. This may be prone to self-report bias. Another limitation was missing 77 readings of HbA1c which might have underestimated the effect of DRD on glycemic control; however, the minimum sample size required to test the correlation between DRD and HbA1c was exceeded in the current study.
5. Conclusions
DRD and low SRAT are commonly reported among patients with DM and both are indirectly correlated. SRAT was found to be mediating the negative DRD’s effect on glycemic control in the Saudi population, hence, these findings highlight the clinical role of DRD and SRAT and help provide better understanding of the process by which distress can affect the outcomes of DM management. The implications of this study for policy suggests that addressing DRD in patients with DM may improve management outcomes through improvement in their SRAT. Therefore, mechanisms for the identification and diagnosis of DRD among DM patients in the study population is strongly recommended.
Ethics approval and consent to participate
A written informed consent was used in this study. The patients were invited to the study & a clear description of the study objectives was given. Also, participation was completely voluntary with participant full choice to withdraw at any time of the research. The study was approved from the Institutional Review Board at Princess Nourah Bint Abdulrahman University (Approval letter number 16-0038).
Consent for publication
Not applicable.
Availability of data and material
Data are available on reasonable request from the primary investigator (AF) after approval from the Institutional Review Board at Princess Nourah Bint Abdulrahman University.
Competing interests
All authors declared no conflicts of interests
Funding
This study is funded by Princess Nourah bint Abdulrahman University Researchers Supporting Project (number PNURSP2022R21) Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia.
We would like to thank all participants of this study for participation in our study, and we extend our gratitude to Dr. Ghadeer Alsheikh for supporting the research team.
References
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Yi-Frazier J.P.
Hessler D.
Butler A.M.
Anderson B.J.
Jaser S.
Stress and A1c among people with diabetes across the lifespan.
Diabetes Distress and Care Registry at Tenri Study Group
Diabetes distress, but not depressive symptoms, is associated with glycaemic control among Japanese patients with type 2 diabetes: Diabetes Distress and Care Registry at Tenri (DDCRT 1).
Physical activity advice only or structured exercise training and association with HbA1c levels in type 2 diabetes: a systematic review and meta-analysis.
Prevalence and predictors of depression, anxiety, and stress symptoms among patients with type II diabetes attending primary healthcare centers in the western region of Saudi Arabia: a cross-sectional study.
Depression and anxiety among hypertensive and diabetic primary health care patients. Could patients’ perception of their diseases control be used as a screening tool?.
Diabetes distress but not clinical depression or depressive symptoms is associated with glycemic control in both cross-sectional and longitudinal analyses.
“I did not want to take that medicine”: African-Americans’ reasons for diabetes medication nonadherence and perceived solutions for enhancing adherence.
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