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Determinants of depression and anxiety among type 2 diabetes patients in governments’ hospitals at Harari regional state, Eastern Ethiopia: A multi-center cross-sectional study

BMC Psychiatry volume 23, Article number: 13 (2023) Cite this article

Abstract

Background

Type 2 diabetes mellitus is the most common health problem globally. Depression and anxiety can exacerbate disease complications, make patients suffer more, and increase healthcare costs. Even though, depression and anxiety are common among type 2 diabetes mellitus patients, there have been limited studies conducted about the determinants of depression and anxiety in Ethiopia. Therefore, the purpose of this study was to assess the magnitude and determinants of depression and anxiety symptoms among Type 2 diabetes mellitus patients, attending out-patient treatment at Harari regional state government hospitals, Eastern Ethiopia.

Method

An institutional based cross-sectional study was conducted from March to April at Harari regional state government hospitals in eastern Ethiopia. A total of 421 participants were recruited using the systematic sampling technique. Data was collected by using Afan Oromo version of interviewer-administered structured and semi-structured questionnaires. Depression and Anxiety symptoms were assessed by the Hospital Anxiety and Depression Scale. Bivariate and multivariate logistic regression analysis was done to identify variables related to both depression and anxiety symptoms. The association was described using an adjusted odds ratio and a 95% confidence interval (CI), with P-values of 0.05 used as a cutoff for a significant association in the adjusted analysis.

Result

Out of the 416 participants included in this study, 42.3%, 40.4% had depression and anxiety symptoms, respectively. Being female (Adjusted Odds Ratio = 1.85(1.09–3.15)), no formal education (Adjusted Odds Ratio = 2.65, (1.04–6.73)), age ≥ 70 (Adjusted Odds Ratio = 2.88 (1.28–6.48)), family history of mental illness (Adjusted Odds Ratio = 1.71 (1.35–3.82)) and poor social support (Adjusted Odds Ratio = 2.35(1.12–6.03)) were statistically associated with depression. While having a family history of mental illness (AOR 1.74(1.03–2.95)), being widowed (AOR = 3.45(1.49–8.01)), and having poor social support (AOR = 2.15(1.12, 4.89)) were statistically significant associated with anxiety at a p-value < 0.05.

Conclusion

Current study results showed that the magnitude of depression and anxiety were relatively high among type 2 diabetes mellitus patients.Having a family history of mental illness and poor social support were statistically associated with both depression and anxiety symptoms. Screening, early detection, and appropriate treatment of depression and anxiety symptoms in type 2 diabetes mellitus patients should be prioritized by health care providers.

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Background

Diabetes mellitus is a chronic metabolic disease characterized by decreasing insulin secretion or due to reduction insulin sensitivity of the cell of the body cell [1]. The International Diabetes Federation (IDF) has released new figures showing that 537 million adults are now living with diabetes worldwide a rise of 16% (74 million) since the previous IDF estimates in 2019. International Diabetes Federation (IDF) projections show that by 2045, 783 million adults will be living with diabetes – or one in eight adults. This would be an increase of 46%, more than double the estimated population growth (20%) over the same period [2, 3]. Type 2 diabetes Mellitus (T2DM) is one of a common health problem with serious medical and economic consequences. It is the third leading cause of disease burden in the worldwide [4]. According to the International Diabetes Federation (IDF), the magnitudes of type 2 diabetes mellitus in Ethiopia is steadily increasing with 3.5% in 2011, 4.36% in 2013, and 7.4% in 2015 making one of the top four countries with the highest adult diabetic populations in sub-Saharan Africa [5, 6].

The co-occurrence, of biological, psychological and psychosocial issues can complicate the diagnosis and management of diabetes mellitus [7]. Depression is common co-morbid conditions that exacerbate the progression of diabetes-related complications and more doubles the risk of depression compared to the general population and It has been reported that depression is twice as common in individuals with type 2 diabetes [8,9,10]. More than fifty percent (52.5%) of patients who had DM for > 20 years were depressed [11, 12]. A growing evidence showed that depression among type 2 diabetes mellitus patients worsen adherence to dietary, medication, physical inactivity and metabolic control which intensify diabetic complications, disease severity and increases health-care expenditures, there by lowers patients’ quality of life [13].

Anxiety is subjective, a vague, non-specific feeling of uneasiness, apprehension, tension, excessive nervousness, and a sense of impending doom, irrational avoidance of objects or situation and anxiety attack [14]. The anxiety disorders make up one of the most common groups of psychiatric disorders and the national co-morbidity study reported that one of four persons met the diagnostic criteria for at least one anxiety disorder and presence of anxiety symptoms significantly impairs the health related quality of life among those with diabetes type 2 mellitus patients [15].

People with diabetes are twice as likely to be diagnosed with anxiety and depression than those without diabetes [11, 16]. Different studies revealed that gender, age, education, diabetes complications and poor glycemic control were related to anxiety and depression in people with T2DM [11, 16,17,18]. Comorbid depression and anxiety are associated with negative health outcomes, such as increased diabetes-related complications [17], increased physical morbidity, higher blood glucose levels [11, 16], poor quality of life [19] and premature death, as compared with depression or anxiety alone [20]. Poor glycemic control and functional impairment due to increasing diabetes complications may cause or worsen depression and anxiety in patients [9, 21, 22].

Despite the fact that 80% of people with type 2 diabetes mellitus live in low and middle-income countries, many studies on depression and anxiety symptoms among type 2 diabetes mellitus patients were conducted in the developed world [22]. Moreover, only a few studies have been conducted in Africa, particularly in Ethiopia. There is a little data about determinants of depression and anxiety among type 2 diabetes mellitus patients which has become the main problem for intervention to reduce the impact of depression and anxiety among type 2 diabetes mellitus patients, and there has been limited study done on the prevalence of depression and anxiety among comorbid type 2 diabetes mellitus patients in Ethiopia, including our study area. Therefore, the aim of this study is to determine of the magnitudes and determinants depression and anxiety symptoms among type 2 diabetes mellitus patients attending out-patient treatment at government hospitals in Harari regional state, Eastern, Ethiopia.

Methods and materials

Study design, setting and period

An institutional-based cross-sectional study design was conducted in Harari regional state among three government hospitals, which are Hiwot Fana Specialized University Hospital, Jugal, and Harari Federal Police Hospital, from March to April 2022. According to a Harari Regional Health Office report, approximately 25,000 diabetes patients were recently receiving follow-up care. Every month, approximately 873 type 2 diabetes mellitus patients visit Hiwot Fana Specialized University Hospital, as well as Jugal and Harari Federal Police Hospitals, for follow-up.

Eligible criteria

All adults (age ≥ 18 years) with type 2 diabetes mellitus patients, who were in an out-patient treatment care of the hospitals during the study period, were included in the study. Patients who had critical health conditions (uncertain prognosis, vital signs are unstable, there are major complications) and those patients unable to communicate properly were excluded.

Sample size determination and sampling procedure

The adequate sample size was calculated by using a single population proportion formula with the following statistical assumptions: n = the minimum sample size required, p = the estimated proportion of depression, z = the standard value of a confidence level of alpha = 95%, d = the margin of error between the sample and the population (0.05). For this study p = 47%, which is the magnitude of depression among type two diabetes mellitus patients in southwest Ethiopia [15].

Accordingly, adding 10% for the non-response rate gives the total calculated sample size of 421. Then, the number of patients was proportionally allocated among the government hospitals. Finally, eligible patients were selected using a systematic random sampling technique with K-value of 2 after proportional allocation was completed for each hospital, K = N/n, 873/421≈2 with a k = 2. The first study participant was selected by a lottery method (manual lottery) from each hospital independently, and then the next study participants were selected at a regular interval (every two) individual.

Variables of study and measurements

Dependent variable

Status of depression symptoms (yes/no) and anxiety symptoms (yes/no).

Independent variables

Socio-demographic variables (sex, age in years, marital status, religion, occupational status, educational status, residence, and average monthly income in Ethiopian birr); clinical factors (family history of mental illness, family history of diabetes mellitus, diabetic complications, Body mass index, Age onset of illness, glycemic control, physical activity, and comorbid medical illness), substance-related factors (current and lifetime substance use of alcohol, tobacco, Khat, and cannabis/ hashish); and psychosocial factors (social support).

Data collection instruments and procedure

Face-to-face interviews were used to collect data using structured and semi-structured questionnaire and a review of patients’ charts. Sociodemographic characteristics’ of participants were collected by structured questionnaire that adapted from different literature. All variables were categorical except age which was collected by close ended questionnaire. Depression and Anxiety was assessed by Hospital anxiety and depression scale. Hospital anxiety and depression scale was used and validated in Ethiopia with internal consistence of 0.78, for anxiety sub-scale 0.76, for depression sub-scale and 0.87 for the full version hospital anxiety and depression scale. It is commonly used to screen for anxiety and depression symptoms, and it has 14 item questions which are divided into two parts, which is a 7- item sub-scale for each depression and anxiety symptoms. The items are rated on a four-point Likert scale which ranges from 0 to 3 with maximum and minimum score of 0 and 21 receptively. If the participant scores ≥ 8 for each of the depression and anxiety sub-scale questions, were considered as the participant has anxiety and depression, respectively [23].

Social support was assessed by Oslo social support scale (Oslo-3) containing three items. Social support was collected by the Oslo-3 item of the social support scale. It is a 3 item questionnaires, commonly used to assess social support and it has been used in several studies. The sum score scale ranged from 3–14, which had 3 categories: poor support 3–8, moderate support 9–11, and strong support 12–14 [24]. It was used in different study and validated in Ethiopia [25].

Substance-related factors were assessed by the Alcohol, Smoking, and Substance Involvement Screening Test(ASSIST), which is a brief screening questionnaire developed and validated by the world health organization (WHO) to find out about people’s use of psychoactive substances was used to assess current and ever substance use history of the subject [26].

Glycemic control was defined according to American Diabetes Recommendation Venus Blood draw for measurement of Glycated hemoglobin (HbAlc). Poor glycemic control was evaluated (HbAlc: < 7% versus ≥ 7% whereas good glycemic control, if patients score 70–130 mg/dl of fasting blood glucose upon measurement of three consecutive visits [27,28,29].

Physical activity: Physical activity was assessed by 2 items of days in the last seven day in week. Then, the responses were added up (range, 0–14). Participants who scored ≥ 8 were coded as adhering to the physical activity recommendations [30].

Data quality control

Data collectors and supervisors were trained for four days on the data collection approach of the study. The questionnaire was translated into local language, Afan Oromo, by language experts and back-translated into English by another person to check for consistency. A pretest was conducted on 21(5%) of the sample size at Haramaya General Hospital to see the applicability of the instruments, and feedback was incorporated into the final tool to improve the quality. The result was not included in the results of this study. Collected data was checked daily for completeness and consistency of filled questionnaires. All data collectors and supervisors were adherent to COVID-19 prevention protocol.

Data processing and analysis

The data were coded, cleaned, and entered into Epi Data version 4.6.0.2 which was then exported to SPSS (Statistical Package for Social Science) version 20 for analysis. Bivariable and multivariable logistic regression analysis was performed to identify factors associated with an outcome variable. All variables with a p-value less than 0.05 in bivariable analysis were entered into the multivariable logistic regression analysis. A p-value of < 0.05 was considered statistically significant, and the adjusted odds ratio (AOR) with a 95% confidence interval (CI) was calculated. The goodness of fitness was checked by the Hosmer-Lemshow test.

Ethical consideration

The study was carried out under consideration of the Helsinki Declaration of medical research ethics [31] .Ethical clearance was obtained from the Institutional Health Research Ethics Review Committee (IHRERC) of Haramaya University College of Health and Medical Sciences with reference number IHREREC/060/2022. A formal letter of permission and support was provided to all three government hospitals in which the study was conducted. Informed, voluntary, written, and signed consent was obtained from the heads of the respective hospitals. Participants were informed about the aim of the study and the advantage of the study; confidentiality, there was no risk of being participants, and they had full right to stop in the middle of the interview. Oral and written informed consent was taken from each participant before data collection began. Confidentiality was maintained at all levels of the study through anonymous data collection. During data collection, the COVID-19 prevention protocol was strictly followed.

Results

Socio-economic characteristics of participants

Out of the 421 study participants, 416 patients were recruited in the study with response rate (98.8%). The median age of the respondents was 53.5 with inter quartile range (IQR, 45–62) years. Among respondents, around half218 (52.4%) were male, and three-fourth, 314 (75.5%) were married. Nearly one in three, 133(32%) of study participants were self-employed and attended secondary school [9,10,11,12] education while most of them 346 (83.2) and 394 (94.7%) were live in urban and with their families respectively, as shown below in (Table 1).

Table 1 Socio-demographic characteristics of patients with type 2 diabetes mellitus attending Government hospitals in Harari regional state, East Ethiopia (n = 416)
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Clinical, substance use and psychosocial characteristics of the respondents

Out of 416 participant, 134(32.2%) of the respondents had up to one year duration of illness whereas 55 (13.2%) of the study participants had complication of diabetes mellitus. From all study participants 130(31.2%) had good glycemic control, 154 (37.0%) had normal body mass index whereas 336 (80.8%) of participants had regular physical activity. Around one in three study participants 133(32.0%) and 134(32.2%) were use only insulin for diabetic treatment and 50–59 age range while disease onset. Nearly half of study participants, 215 (51.7%) have strong social support and 234(56.3%) were ever Khat user as shown below in (Table 2).

Table 2 Clinical, substance use and psychosocial characteristics of patients with type 2 diabetes mellitus attending Government hospitals in Harari region state, East Ethiopia (n = 416)
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Factors associated with depression among patients with type 2 diabetes mellitus

In Bivariate logistic regression analysis, age ≥ 70, being female, divorced, widowed, no attend formal education, monthly income less than 1000, having family history of mental illness, having family history of DM, age of start disease less than 50 years,, ever substance use, ever Khat use, poor and moderate were factors significantly associated with depression. However, in the multivariate logistic regression analysis, variables like age ≥ 70, being female, having no formal education, having monthly income less than 1000 EBT, having family history of mental illness, and having poor social support were significantly associated with depression at a p value of 0.05.

In this study, the odds of having depression among respondents with age ≥ 70 were about 2.88 times higher as compared to participants those age range 18–39 (AOR = 2.88 (1.28–6.48)), and the odds of having depression among female participants was 1.85 times higher as compared to male respondents (AOR = 1.85(1.09–3.15)).

Participants who did not attend formal education had 2.65 times the odds of having depression as those who had a degree or higher educational status (AOR = 2.65, (1.04–6.73)). The findings of this study indicated that the odds of having depression among participants who had family history of mental illness and poor social support were about 1.71 and 2.35 times higher as compared to participants who had no family history of mental illness and had strong social support (AOR = 1.71 (1.35–3.82)), (AOR = 2.35 (1.12–6.03)) respectively as shown in the table below (Table 3).

Table 3 Factors associated with depression among patients with type 2 diabetes mellitus attending government hospitals in Harari regional state East Ethiopia (n = 416)
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Factors associated with anxiety among patients with type 2 diabetes mellitus

In bivariate logistic analysis, age greater than 40, divorced,widowed, attending secondary school (grade 9–12), monthly income less than 1000, greater than one year’s duration of illness, having family a history of mental illness, ever using Khat, and having moderate and poor social support were factors significantly associated with anxiety. However, multivariate analysis indicated, being widowed, family history of mental illness and poor social support were significantly associated with anxiety at a p value of 0.05.

In this study, participants with a family history of mental illness had 1.74 times the odds of having anxiety as those who did not have a family history of mental illness (AOR: 1.74 (1.03–2.95)). Odds of having anxiety among participants with being widowed were 3.45 times higher as compared to those being married participants (AOR = 3.45(1,49–8.01)) and odds of having anxiety among participants who had poor social support were 2.15 times higher as compared to those who had strong social support (AOR = 2.15, 95% CI: 1.12, 4.89) as shown below in (Table 4).

Table 4 Factors associated with anxiety among patients with type 2 diabetes mellitus attending government hospitals in Harari regional state East Ethiopia (n = 416)
Full size table

Discussion

This study finding show that significant number, 42.3% and 40.4% of type 2 diabetes mellitus patients had depression and anxiety symptoms respectively. This prevalence might be due impact of physical illness, comorbid innless and COVID-19. Having family history of mental illness and poor social support were statistically associated with both depression and anxiety.

The magnitude of depression symptoms among type 2 diabetic mellitus patients was 42.3% (95% CI, 37.7–47.1). This finding was in line with the study conducted in Mexican city 39% [32], South African 46% [33], Sudan 44% [34] and 47% at Ambo general hospital south west Ethiopia [15].

However, the result of this study,42.3% of depressive symptoms was lower than the study conducted in Nepal 57.8% [35], southern Iran 59% [36], Xuzhou, China 56.1% [37] and 47.9% Faisalabad [38]. The possible reason for the discrepancy might be due to the assessment tools for depression, Hospital Anxiety and Depression Scale (HADS) was used in this study but the study done in Nepal was used the Patient Health Questionnaire-9 (PHQ- 9) [35], Beck Depression Inventory in southern Iran [36], Depression Anxiety and Stress scale [38] and the Zung Self-Rating Depression Scales was used in China [37]. Other possible reason might be study design, an instructional based cross-sectional study was used in this study but study done in China and southern Iran were used community based cross-sectional and case–control respectively and also the study participants, environmental factors, sociocultural difference and age of participant.

On the other hand, the finding of current study was higher than the study done in Lithuania 22.4% [18], Kenya 32.3% [39] Sudan 35.6% [40] and south west Ethiopia 34.9% [41]. The possible reason for the discrepancy might be instrument used, which was in this study used Hospital Anxiety and Depression Scale (HADS), but the study done in Kenya [39], was used the Patient Health Questionnaire-9 (PHQ- 9), Beck Depression Inventory (BDI) scale questionnaire was used in southwest Ethiopia [41] and Patient Health Questionnaire-9 (PHQ- 9) was used in Eastern Sudan [40]. Study participants, setting and sociocultural difference might be also another possible reason for the discrepancy.

The prevalence of the anxiety symptoms among type 2 diabetic patient in this study was found to be 40.4%( 95% CI 35.6–45.4). This study result was in line with the study conducted in Saudi Arabia 45.45% [42], China 43.5% [37] and at Ambo General Hospital, southwest Ethiopia 44.2% [15].

However, the result of this study,40.4% Anxiety symptoms was lower than the studies conducted in Nepal 49.7% [35], southern Iran 62% [36], Faisalabad 69.6% [43] and Saudi Arabia 51.3% [44]. The possible reason for the discrepancy might be due to data collection tools for anxiety, which was this study used Hospital Anxiety and Depression Scale (HADS) but the study done in Nepal was used the Generalized Anxiety Disorders (GAD-7), Hamilton Anxiety questionnaires in southern Iran [36], Depression Anxiety and Stress scale (DASS) in Faisalabad [43]. The other possible reason for discrepancy might be the study participants, sample size and sociocultural difference of participant.

However, the finding of this study was higher than the studies conducted in Lithuania [18], North India 27.6% [45] and south Africa 32% [33]. The possible reason for variation might be due study design which was this study used cross-sectional study but cohort study was used south Africa [33] and instrument used which was this study used Hospital Anxiety and Depression Scale (HADS) but northern India [45] used Hamilton Anxiety Rating Scale.

Regarding factors associated with depression among type 2 diabetic patients, age ≥ 70 (older) of participants was significantly associated with depression. This finding was supported by studies conducted in Nepal [35], Xuzhou, China [37], South African [33], Kenya [39], and at Ambo general hospital [15]. This could be due to physical inactivates among elder patients. It is the fact that physical activity is a protective barrier against depression and the development of other psychological illnesses due to an decrease release of endorphins and brain neurotransmitters during exercise [46]. The other possible explanation is older patients faces many challenges including family or social isolation, different co-morbid diseases and disabilities.

The odds of having depression symptoms among respondents with female participants were 1.85 times higher when compared to participants with male gender. This result was supported by a studies conducted in Mexican [32], Nepal [35], China [37], South Africa [33],Sudan [40]and southwest Ethiopia [41]. The possible justification female were grater vulnerable to other psychosocial in additional to hormonal effect [8, 46]. Other possible reason might be related to depression are more common or two times as compared to male [46].

Regarding to family history of mental illness, participants who had family history of mental illness was 1.71and 1.74 times to had depression and anxiety respectively as compared to those who had no family history of mental illness. This was congruent with study carried out in Nepal [35] the possible reason might be family history of mental disorders are one the risk factor for mental disorder (the genetic effect) especially mood disorders which is if one parent has a mood disorder, a child will have a risk of between 10 and 25 percent for mood disorder [46].

The odds of having depression and anxiety symptoms among respondents with poor social support were 2.35 and 4.01 times higher as compared to those who had strong social support respectively. This finding was similar with prior studies conducted in Nepal [35], southwest Ethiopia [41] and at Ambo general hospital [15]. This might be a feeling of unsupported (isolated) and somatic illness (like diabetes mellitus) leads to increase psychosocial stress, in contrary good social support is critical for those in good health in reducing the risk of depression [47].

The odd of having anxiety symptoms among participants with being widowed was 3.45 times higher as compared to participants those being married. This finding was line with the studies conducted in Saudi Arabia [44] and South African [33]. The possible justification could be, widowed people might be experience anxiety symptoms like feelings of hopelessness, and worthlessness due to a lack of social support from their wife or husband.

Limitations of the study

The retrospective items used in the questionnaire may have incurred recall bias, like duration of illness, duration of treatment, and types of medication. The cause-effect relationship between outcome variables and predictive variables was difficult to clarify because of the cross-sectional nature of the study. The COVID-19 pandemic might also affect the results of this study.

Future directions

Based on the limitations of this study, we recommend that interested researchers in the fields of mental health and public health conduct longitudinal studies to investigate the magnitude of depression and anxiety symptoms. Furthermore, longitudinal studies are recommended to explore the cause-effect relationship between outcome variables and predictive variables.

Conclusions

The findings of this study showed that the magnitude of depression and anxiety symptoms was relatively high, according to global estimation, among type 2 diabetes mellitus patients. Being female, age ≥ 70, not attending formal education, having average monthly income < 1000 EBT, having a family history of mental illness, and having poor social support were statistically associated with depressive symptoms whereas being widowed, having family history of mental illness and poor social support were statistically associated with anxiety symptoms. An effort should be taken by health care workers to strengthen and disseminate health education programs for diabetic patients and screening, early identification, and providing appropriate intervention for depression and anxiety among type 2 diabetes mellitus patients should be a great concern for the health care providers. It is better to establish health care programs, assessments and monitoring for people with type 2 diabetes mellitus who have a family history of mental illness, poor social support and patients will be treated early as soon as early identified. Intervene for this identified determinant was important for halt the distribution of depression and anxiety and reduce the complication of type 2 diabetes mellitus.

Availability of data and materials

The original contributions presented in the study are included in the article.

Abbreviations

T2DM:

Type 2 diabetes mellitus

HADS:

Hospital Anxiety and Depression Scale

ASSIST:

Alcohol, Smoking and Substance Involvement Screening Test

WHO:

World health organization

References

  1. Roupa Z, Koulouri A, Sotiropoulou P, Makrinika E, Marneras X, Lahana I, et al. Anxiety and depression in patients with type 2 diabetes mellitus, depending on sex and body mass index. Health Sci J. 2009;3(1):32–40.

    Google Scholar 

  2. Shaw JE, Sicree RA, Zimmet PZ. Global estimates of the prevalence of diabetes for 2010 and 2030. Diabetes Res Clin Pract. 2010;87(1):4–14.

    Article  CAS  Google Scholar 

  3. 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. Diabetes Res Clin Pract. 2019;157:107843.

    Article  Google Scholar 

  4. Xu G, Liu B, Sun Y, Du Y, Snetselaar LG, Hu FB, et al. Prevalence of diagnosed type 1 and type 2 diabetes among US adults in 2016 and 2017: population based study. bmj. 2018;362.

  5. L’heveder R, Nolan T. International diabetes federation. Diabetes Res Clin Pract. 2013;101(3):349–51.

    Article  Google Scholar 

  6. Atlas D. International diabetes federation. IDF Diabetes Atlas, 7th ed. Brussels, Belgium: International Diabetes Federation. 2015;33.

  7. Taneja N, Adhikary M, Chandramouleeswaan S, Kapoor SK. Prevalence of common mental disorders among patients with diabetes mellitus and hypertension in an urban east delhi slum–a cross sectional study. Hindu. 2015;44:43–6.

    Google Scholar 

  8. Tiwari G, Tiwari R, Sriwastawa B, Bhati L, Pandey S, Pandey P, et al. Drug delivery systems: An updated review. Int J Pharm Investigation. 2012;2(1):2.

    Article  Google Scholar 

  9. Shamsaei F, Cheraghi F, Allahverdipour H. Depression in diabetic patients. J Res Health Sci. 2006;6(2):39–43.

    Google Scholar 

  10. Poongothai S, Anjana RM, Radha S, Sundari BB, Shanthirani C, Mohan V. Epidemiology of Depression and its Relationship to Diabetes in India. J Assoc Physicians India. 2017;65:60.

    Google Scholar 

  11. Roy T, Lloyd CE. Epidemiology of depression and diabetes: a systematic review. J Affect Disord. 2012;142:S8–21.

    Article  Google Scholar 

  12. El Mahalli AA. Prevalence and predictors of depression among type 2 diabetes mellitus outpatients in Eastern Province, Saudi Arabia. Int J Health Sci. 2015;9(2):119.

    Google Scholar 

  13. Tran NMH, Nguyen QNL, Vo TH, Le TTA, Ngo NH. Depression among patients with type 2 diabetes mellitus: prevalence and associated factors in Hue City Vietnam Diabetes Metabolic Syndrome and Obesity. Targets The. 2021;14:505.

    Google Scholar 

  14. Sadock BJ, Sadock VA. Kaplan and Sadock's pocket handbook of clinical psychiatry. Lippincott Williams & Wilkins; 2010.

  15. Tiki T. Prevalence and associated factors of depression among type 2 diabetes mellitus patients on follow up at ambo general hospital, Oromia regional state, Ethiopia, institutional based cross sectional study. J Depress Anxiety. 2017;6(01):2167-1044.1000259.

  16. Bouwman V. adriaanse Mc, van't riet e, Snoek FJ. dekker JM and nijpels G: depression, anxiety and glucose metabolism in the general dutch population: The new Hoorn Study PloS one. 2010;5:e9971.

  17. Öztürk ZA, Yesil Y, Kuyumcu ME, Savas E, Uygun Ö, Sayıner ZA, et al. Association of depression and sleep quality with complications of type 2 diabetes in geriatric patients. Aging Clin Exp Res. 2015;27(4):533–8.

    Article  Google Scholar 

  18. Mikaliūkštienė A, Žagminas K, Juozulynas A, Narkauskaitė L, Sąlyga J, Jankauskienė K, et al. Prevalence and determinants of anxiety and depression symptoms in patients with type 2 diabetes in Lithuania. Med Sci Monit. 2014;20:182.

    Article  Google Scholar 

  19. Egede LE. Diabetes, major depression, and functional disability among US adults. Diabetes Care. 2004;27(2):421–8.

    Article  Google Scholar 

  20. Park M, Katon WJ, Wolf FM. Depression and risk of mortality in individuals with diabetes: a meta-analysis and systematic review. Gen Hosp Psychiatry. 2013;35(3):217–25.

    Article  Google Scholar 

  21. Balhara YPS, Sagar R. Correlates of anxiety and depression among patients with type 2 diabetes mellitus. Indian journal of endocrinology and metabolism. 2011;15(Suppl1):S50.

    Article  Google Scholar 

  22. Khan P, Qayyum N, Malik F, Khan T, Khan M, Tahir A. Incidence of anxiety and depression among patients with type 2 diabetes and the predicting factors. Cureus. 2019;11(3).

  23. Reda AA. Reliability and validity of the Ethiopian version of the hospital anxiety and depression scale (HADS) in HIV infected patients. PLoS ONE. 2011;6(1):e16049.

    Article  CAS  Google Scholar 

  24. Kocalevent R-D, Berg L, Beutel ME, Hinz A, Zenger M, Härter M, et al. Social support in the general population: standardization of the Oslo social support scale (OSSS-3). BMC psychology. 2018;6(1):1–8.

    Article  Google Scholar 

  25. Duko B, Ayano G, Bedaso A. Depression among pregnant women and associated factors in Hawassa city, Ethiopia: an institution-based cross-sectional study. Reprod Health. 2019;16(1):1–6.

    Article  Google Scholar 

  26. Group WAW. The alcohol, smoking and substance involvement screening test (ASSIST): development, reliability and feasibility. Addiction. 2002;97(9):1183–94.

    Article  Google Scholar 

  27. Marathe PH, Gao HX, Close KL. American Diabetes Association Standards of Medical Care in Diabetes 2017. Wiley Online Libr; 2017.

  28. Association AD. Standards of medical care in diabetes–2014. Diabetes Care. 2014;37:S14–80.

    Article  Google Scholar 

  29. Tadele A, Getachew T, Defar A, Taye G, Molla G, Getachew F, et al. Effect of khat consumption on blood biochemical parameters: evidences from the Ethiopian non communicable diseases STEPS Survey, 2015. Ethiopian J Public Health Nutr. 2021;4(2):129–35.

    Google Scholar 

  30. Warren-Findlow J, Seymour RB. Prevalence rates of hypertension self-care activities among African Americans. J Natl Med Assoc. 2011;103(6):503–12.

    Google Scholar 

  31. Association WM. World Medical Association Declaration of Helsinki. Ethical principles for medical research involving human subjects. Bull World Health Organ. 2001;79(4):373.

    Google Scholar 

  32. Téllez-Zenteno JF, Cardiel MH. Risk factors associated with depression in patients with type 2 diabetes mellitus. Arch Med Res. 2002;33(1):53–60.

    Article  Google Scholar 

  33. Ramkisson S, Pillay BJ, Sartorius B. Anxiety, depression and psychological well-being in a cohort of South African adults with Type 2 diabetes mellitus. S Afr J Psychiatry. 2016;22(1).

  34. Mirghani H, Mohammed O, Saadallah A. Prevalence of depression among Sudanese patients with type-2 diabetes mellitus. Sudan Journal of Medical Sciences. 2014;9(3):151–5.

    Google Scholar 

  35. Sharma K, Dhungana G, Adhikari S, Bista Pandey A, Sharma M. Depression and Anxiety among Patients with Type II Diabetes Mellitus in Chitwan Medical College Teaching Hospital, Nepal. Nursing research and practice. 2021;2021.

  36. Dehesh T, Dehesh P, Shojaei S. Prevalence and associated factors of anxiety and depression among patients with Type 2 diabetes in Kerman, Southern Iran. Diabetes, Metabolic Syndrome and Obesity: Targets and Therapy. 2020;13:1509.

    Google Scholar 

  37. Sun N, Lou P, Shang Y, Zhang P, Wang J, Chang G, et al. Prevalence and determinants of depressive and anxiety symptoms in adults with type 2 diabetes in China: a cross-sectional study. BMJ Open. 2016;6(8):e012540.

    Article  Google Scholar 

  38. Rehman A, Kazmi S. Prevalence and level of depression, anxiety and stress among patients with type-2 diabetes mellitus. Ann Pak Inst Med Sci. 2015;11(2):81–6.

    Google Scholar 

  39. Kanu J. Prevalence and severity of co-morbid depression in ambulatory type 2 diabetes patients at the Kenyatta national hospital (knh): University of Nairobi; 2015.

  40. Omar SM, Musa IR, Idrees MB, Adam I. Prevalence of depression and associated factors among patients with type 2 diabetes mellitus in eastern Sudan. BMC Psychiatry. 2021;21(1):1–8.

    Article  Google Scholar 

  41. Geleta B, Dingata S, Emanu M, Kebede E, Eba L, Abera K. Prevalence of Depression and Associated Factors among Type 2 Diabetes Patients attending hospitals in Ilu AbaBor and Bunno Bedelle Zones, South West Ethiopia, 2020: A Cross Sectional Study. J Depress Anxiety. 2021;9:388.

    Google Scholar 

  42. Alharithy MK, Abdalgader OR, Alobaylan MM, Alsugair ZO, Alswat KA. Anxiety prevalence in type 2 diabetes patients in Taif Saudi Arabia. Anxiety. 2019;8(2):88–92.

    Google Scholar 

  43. Sadeghi M, Safari-Mousavi SS, Farhadi M. The role of psychological flexibility and self-compassion in predicting depression, anxiety and stress in patients with type 2 diabetes. Journal of Isfahan Medical School. 2017;35(452):1468–75.

    Google Scholar 

  44. AlBekairy A, AbuRuz S, Alsabani B, Alshehri A, Aldebasi T, Alkatheri A, et al. Exploring factors associated with depression and anxiety among hospitalized patients with type 2 diabetes mellitus. Med Princ Pract. 2017;26(6):547–53.

    Article  Google Scholar 

  45. Rajput R, Gehlawat P, Gehlan D, Gupta R, Rajput M. Prevalence and predictors of depression and anxiety in patients of diabetes mellitus in a tertiary care center. Indian journal of endocrinology and metabolism. 2016;20(6):746.

    Article  Google Scholar 

  46. Sadock BJ. Kaplan & Sadock's synopsis of psychiatry: behavioral sciences/clinical psychiatry. 2007.

  47. Ismail Z, Mohamad M, Isa MR, Fadzil MA, Yassin SM, Ma KT, et al. Factors associated with anxiety among elderly hypertensive in primary care setting. J Ment Health. 2015;24(1):29–32.

    Article  Google Scholar 

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Acknowledgements

We would like to acknowledge the Haramaya University for financially supporting the collection of data for this study. We extend our gratitude to data collectors and study participants for their time and effort

Author information

Authors and Affiliations

  1. Department of Psychiatry, College of Health and Medical Sciences, Haramaya University, Harar, Ethiopia

    Kabtamu Nigussie, Tilahun Bete & Dawud Wadaje

  2. Department of Nursing, College of Health and Medical Science, Haramaya University, Harar, Ethiopia

    Addisu Sertsu & Lemesa Abdisa

  3. Department Epidemiology and Biostatistics, School of Public Health, College of Health and Medical Science, Haramaya University, Harar, Ethiopia

    Galana Mamo Ayana

  4. Department of Public Health, College of Health and Medical Science, Haramaya University, Harar, Ethiopia

    Yadeta Dessie

  5. Department of Public Health, College of Health Science, Mettu University, Mettu, Ethiopia

    Gebiso Roba Debele

  6. Department of Midwifery, College of Health and Medical Science, Haramaya University, Harar, Ethiopia

    Abraham Negash

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  1. Kabtamu Nigussie
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Contributions

KN was the principal investigator of the study and was involved from inception to design acquisition of data, analysis, and interpretation, and drafting and editing of the manuscript.AS, GM, LA,TB,YD,GR,DW and AN, was involved in the reviewing of the proposal, tool evaluation, interpretation, and critical review of the draft manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Kabtamu Nigussie.

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Ethics approval and consent to participants

The study was carried out in accordance with relevant guidelines and regulations of the Helsinki Declaration of medical research ethics(31). It involving human participants were reviewed and approved by Institutional Health, Research Ethics Review Committee of College of Health and Medical Sciences, Haramaya University with reference number IHREREC/060/2022. The participants provided their oral and written informed consent to participate in this study. A formal letter of permission and support was provided to all the three government hospitals in which the study was conducted. Participants were informed about the aim of the study and the advantage of the study. Oral and written informed consent was taken from each participant before data collection began. Confidentiality was maintained at all levels of the study through anonymous data collection.

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Not applicable.

Competing interests

The authors declare that they have no competing interests.

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Nigussie, K., Sertsu, A., Ayana, G.M. et al. Determinants of depression and anxiety among type 2 diabetes patients in governments’ hospitals at Harari regional state, Eastern Ethiopia: A multi-center cross-sectional study. BMC Psychiatry 23, 13 (2023). https://doi.org/10.1186/s12888-022-04494-x

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Keywords

BMC Psychiatry

ISSN: 1471-244X

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