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HOME > Osong Public Health Res Perspect > Volume 6(4); 2015 > Article
Original Article
Depression among Korean Adults with Type 2 Diabetes Mellitus: Ansan-Community-Based Epidemiological Study
Chan Young Park, So Young Kim, Jong Won Gil, Min Hee Park, Jong-Hyock Park*, Yeonjung Kim*
Osong Public Health and Research Perspectives 2015;6(4):224-232.
DOI: https://doi.org/10.1016/j.phrp.2015.05.004
Published online: July 29, 2015
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aCourse of convergence in Health and Biomedicine Program in Health Policy, College of Medicine, Chungbuk National University, Cheongju, Korea

bDivision of Genome and Epidemiology, Center for Genome Science, Korea National Institute of Health, Cheongju, Korea

cRegional Cardiocerebrovascular Center, Chungbuk National University Hospital, Cheongju, Korea

dDepartment of Medicine Graduate School, Chungbuk National University, Cheongju, Korea

∗Corresponding authors. jonghyock@gmail.comyeonmaru@gmail.com
• Received: December 29, 2014   • Revised: April 20, 2015   • Accepted: May 20, 2015

Copyright © 2015 Korea Centers for Disease Control and Prevention. Published by Elsevier Korea LLC. All rights reserved.

  • Objectives
    There are an increasing number of studies being carried out on depression in patients with diabetes. Individuals with diabetes have been reported as having a higher prevalence of depression compared to those without diabetes. However, only a few studies involving Korean patients have been conducted. The aims of this study were to examine the prevalence of depression and to find various risk factors according to the degree of depression among Korean patients with Type 2 diabetes mellitus (T2DM).
  • Methods
    An Ansan-community-based epidemiological study was conducted from 2005 to 2012. The total number of participants in this study was 3,540, from which patients with diabetes (n = 753) have been selected. The presence of depression was evaluated using the Beck Depression Inventory total score.
  • Results
    The prevalence of depression was 28.8%. The mean age of participants was 55.5 ± 8.2 years. We divided the participants into three groups (without-depression, moderate-depression, and severe-depression groups) to examine the depression prevalence among Korean T2DM patients. The unemployed participants had 2.40 [95% confidence interval (CI) 1.21–4.76], the low-income participants had 2.57 (95% CI 1.52–4.35), the participants using an oral diabetes medicine or insulin had 2.03 (95% CI 1.25–3.32), the participants who are currently smoking had 2.03 (95% CI 1.10–3.73), and those without regular exercise had 1.91 (95% CI 1.17–3.14) times higher odds of depression in the severe-depression group, compared with the without-depression group.
  • Conclusion
    There was a significant association between depression prevalence and diabetes, and we found various risk factors according to the degree of depression in Korean patients with T2DM.
The World Health Organization has reported that about 350 million people have depression, and about one million people with depression worldwide commit suicide every year. Also, according to the latest cause-of-death statistics (2013) released by the National Statistical Office of Korea, 14,427 out of every 10 million deaths in Korea are attributable to suicide. Suicide is the fourth leading cause of death in Korea [1].
In the Sixth Korea National Health and Nutrition Examination Survey (2013), among people more than 19 years of age, 10.7% (men 6.6%, women 13.7%) experienced depression continuously for more than 2 weeks in a year (Korea age, standardization) [2]. It can be seen that women feel more depressed than men. A history of depression, a family history of depression, a major disease occurrence before the age of 40 years, postmenopausal status [3], body mass index, serum-protein concentration, hemoglobin concentration, smoking, exercise [4], and marital status in the elderly [5] have all been reported as risk factors for depression. Glycated hemoglobin (HbA1c), erectile dysfunction, blood pressure, and waist-to-hip ratio [6] have been reported to be relevant.
In recent years, studies on depression of patients with diabetes have been actively proceeding [7]. Individuals with diabetes have been reported as having a higher prevalence of depression compared to those without the condition. The prevalence of depression in people with diabetes is higher in women 8, 9, unmarried people [5], those with more children [10], and those with low vitamin B6 11, 12. Also, patients with both depression and diabetes have low adherence to diet and exercise instructions, which may contribute to the worsening of their quality of life and the deterioration of their diabetes [13]. One-third of individuals with their first diabetic foot ulcer suffer from clinical depression, and this has been reported to be associated with increased mortality [14]. Diabetes mellitus is also related to childhood obesity [15] and change of lifestyle in the middle-aged and the elderly in Korea 16, 17 with metabolic change [18].
It has been reported that other factors affecting depression in a diabetic patient include age, body mass index, drug increases, neurological disease, retinopathy, sexual dysfunction [19], microvascular and macrovascular complications [20], incident end-stage renal disease [21], and systemic inflammation [10].
There are many previous studies on depression among participants with diabetes. However, studies for the Korean population 8, 22 are rare. The aims of this study were to examine the prevalence of depression and to find various risk factors according to the degree of depression in patients with Type 2 diabetes mellitus (T2DM), especially Koreans.
2.1 Study participants
An Ansan-community-based epidemiological study has been conducted by the Korea National Institute of Health. The participants were selected to reflect the gender and age of the Korean population after randomly extracting 40- to 69-year-old residents in Ansan City. The total number of participants from 2005 to 2012 was 3,540. Patients without diabetes and patients who did not respond to the depression survey items were excluded from the study. Therefore, the total number of study participants was reduced to 753.
2.2 Depression assessment tool
The presence of depression was evaluated using the Beck Depression Inventory (BDI) total score. The BDI, which measures the emotional, cognitive, motivational, and physiological items, is one of the most widely used measures of depression. The instrument consists of 21 items, and the score, which determines the possible degree of depression, ranges from 0 to 63. Higher scores indicate greater depression. There are many opinions regarding the most appropriate cutoff points. In the West, a score of 15 or more is generally considered to indicate depression. However, cutoff points from 16 to 21 may be more appropriate in other populations, including Koreans, because research has shown that the average value of the BDI is higher in these populations than in Westerners [23].
The Depression Clinical Research Center, specified by the Ministry of Health & Welfare, classifies BDI scores as follows: “nondepressed state: 0–9; mild depressive state: 10–15; moderate depressive state: 16–23; and severe depressive state: 24–63.”
The BDI was translated by Lee and Song [24], and it has been used in a number of papers 25, 26, 27, 28 with cutoff scores of ≥16. Therefore, we used the most commonly used cutoff score for BDI of ≥16 to indicate clinical depression.
2.3 Definitions for diagnosing diabetes mellitus
The presence of T2DM is defined as fasting plasma glucose ≥126 mg/dL (7.0 mmol/L) or 2-hour plasma glucose ≥200 mg/dL (11.1 mmol/L), or HbA1c ≥ 6.5% [29]. These criteria are consistent with the Standards of Medical Care in Diabetes of the American Diabetes Association [30].
2.4 Other covariates
The clinical-examination items: low-density-lipoprotein (LDL) cholesterol, lifestyle-related items: alcohol consumption, smoking, and current exercise, and anthropometric-related items: obesity, abdominal obesity, etc., were selected for the analysis.
The cutoff point of the calculated LDL cholesterol [total cholesterol – high-density lipids – (0.2 × triglyceride)] was 130 mg/dL (Korea Society of Lipidology and Atherosclerosis, 2012).
As the minimum cost of living based on a four-person household in 2006 was 1.2 million won (through the announcement of the Department of Health and Human Services, 2006), low income was determined to be < 1.5 million won (the interval containing the 1.2 million won).
The obesity criterion was based on body mass index, ≥25 kg/m2 is defined as Overweight or more (World Health Organization, 2000). The abdominal-obesity criterion was based on waist circumference: women ≥85 cm and men ≥90 cm 31, 32.
2.5 Statistical analyses
Statistical analyses were performed with the aid of SAS software (version 9.3; SAS Institute). The dependent variable was the BDI total score. Statistical comparisons of general-characteristic variables between the without depression (16 < BDI) and with depression [moderate depression (16 ≤ BDI < 24), severe depression (BDI ≥ 24)] were conducted using Chi-square tests for categorical variables and the Kruskal–Wallis test for continuous variables comparing the three groups of participants. Also, according to the depressed state, the participants were divided into three groups, and an ordinal multiple logistic regressions analysis was performed for the three group comparisons. All tests were two tailed, with p < 0.05 considered to indicate statistical significance.
Table 1 shows the general characteristics and the depression prevalence of the study participants with T2DM (n = 753). Of these participants, 28.82% had depression. The mean age of the participants analyzed was 55.48 ± 8.22 [without depression (54.77 ± 7.84) vs. with depression (57.22 ± 8.87)].
We divided participants into three groups [without depression (16 < BDI), moderate depression (16 ≤ BDI < 24), severe depression (BDI ≥ 24)] to determine the depression prevalence of the study participants with T2DM.
Depression (BDI score ≥16) was more prevalent in women than in men (p = 0.003), and in unmarried people than in married people (p = 0.006). Also, the prevalence of depression was higher in the lower-monthly-income participants (p < 0.001), in the lower-level-of-education participants (p < 0.001), in 60 years or older participants (p = 0.023), in people who are taking medicines for diabetes (p < 0.001), in people who are currently smoking (p = 0.082), in patients without regular exercise (p < 0.001), in patients with HbA1c ≥ 0.5 (p = 0.004), and in postmenopausal women (p < 0.001). The p between depression and dietary patterns is as follows: vitamin B6 (p < 0.001), vitamin B2 (p = 0.001), fiber (p < 0.001), and folate (p < 0.001).
In Table 2, the demographic-characteristic odds ratios (ORs) for the 753 participants with T2DM are summarized.
The participants with severe depression were women [OR 2.10, 95% confidence interval (CI) 1.33–3.32], 60 years or older people (OR 1.98, 95% CI 1.12–3.53), married people (OR 2.58, 95% CI 1.38–4.83), jobless people (OR 3.36, 95% CI 1.81–6.25), low-income participants (OR 3.65, 95% CI 2.29–5.84), people with low education level (OR 2.77, 95% CI 1.74–4.41), people using an oral diabetes medicine or insulin (OR 2.32, 95% CI 1.46–3.67), people who are currently smoking (OR 1.65, 95% CI 1.06–2.57), people who exercise regularly (OR 2.19, 95% CI 1.36–3.52), people with HbA1c ≥ 6.5 (OR 1.89, 95% CI 1.19–2.98), and menstrual status (in women) (OR 3.75, 95% CI 1.42–9.93). The ORs for the participants with severe depression linked to dietary patterns (adjusted gender and age) are vitamin B6 = 0.53 (95% CI 0.32–0.89), vitamin B2 = 0.46 (95% CI 0.22–0.93), fiber = 0.85 (95% CI 0.76–0.96), and folate = 0.996 (95% CI 0.993–0.999).
Table 3 shows the risk factors associated with depression among the participants with diabetes. To study depression among Korean Adults with T2DM, an adjusted variables were gender, age, marital status, current job status, monthly income, education duration, diabetes duration, medicine use, current drinking status, current smoking status, regular exercise, obesity, hypertension and HbA1c, comorbid chronic diseases (ordinal multivariate analysis according to the depression status), vitamin B6, vitamin B2, fiber, and folate.
The low-income participants had 2.07 (95% CI 1.23–3.48) times higher odds of depression in the moderate-depression group and 2.46 (95% CI 1.35–4.46) times in the severe-depression group than the without-depression group.
The participants that were being treated with an oral diabetes medicine or insulin had 2.05 (95% CI 1.18–3.55) times higher odds of depression in the moderate-depression group and 2.20 (95% CI 1.13–4.29) times in the severe-depression group than the without-depression group.
Current smokers had 2.40 (95% CI 1.38–4.17) times higher odds of depression in the moderate-depression group and 2.46 (95% CI 1.23–4.90) times in the severe-depression group than the without-depression group.
Those without regular exercise had 1.70 (1.02–2.82) times higher odds of depression in the severe-depression group than the without-depression group.
The causal relationship between diabetes and depression is controversial, but the high prevalence of depression in diabetic patients has been established in various studies. Therefore, a study to examine the prevalence of depression in Korean diabetic patients was conducted. As there are only a few studies involving Korean diabetic patients, it can be said that this study is worthy.
Many studies have reported a prevalence rate of depression among adult diabetic patients ranging from 3.8% to 41.3% 33, 34, 35, 36, 37, 38, and the result (28.82%) of this study is within that range.
The assessment tools for depression used in other studies include the Geriatric Depression Scale [39], Patient Health Questionnaire-2 [8], Epidemiologic Studies Depression Scale [40], Center for Epidemiological Studies-Depression Scale, Hospital Anxiety and Depression Scale, Composite International Diagnostic Interview, Hamilton Depression Rating Scale, and Patient Health Questionnaire-9 9, 20, 36, 38. Here, we used BDI because the assessment methods are easy to do and, due to its high objectivity, BDI is considered the most commonly used assessment tool for depression.
In some studies, LDL cholesterol, obesity [41], and diabetes duration significantly influenced depression, but that was not the case in this study. It seems that the ages of the participants were limited to 43–73 years, and diabetes duration was slightly shorter with 4.02 ± 4.60 years.
Also, comorbid chronic diseases (cancer, kidney disease, hyperlipidemia, coronary disease, and cerebrovascular diseases) were not significant in this study. The number of patients with these diseases seems too few.
The depression and dietary patterns of the diabetic group were studied based on a total of 21 nutrients by adjusting the gender and age. The results show that vitamin B6, vitamin B2, and fiber were found to be significant. Vitamin B6 is a material involved in neurotransmitter synthesis, immune metabolism, and lipid metabolism, and it has been reported in some studies that vitamin B6 deficiency is associated with depression 11, 12. Vitamin B2 enhances the immune system. To our knowledge, no studies have been conducted to show the relationship between depression and vitamin B2 deficiency. This could be a topic of future studies.
The incidence of smoking worldwide is currently high. In this study, the relationship between smoking and severe depression, as well as between the lack of exercise and severe depression, has been established.
The strengths of this study are as follows. (1) Through a review of several papers, items related to depression in the diabetic group have been identified. In particular, using the dietary patterns for the Koreans, there was not study depression in the diabetic group. (2) Study analyses were carried out by dividing participants into three groups to review in detail the risk factors of depression by depression degree. As a result, we found that more severe depression was linked to greater the exposure to risk factors.
The limitations of this study are as follows: (1) this is a cross-sectional study, in which the reason for the causal relationship is difficult to establish; and (2) the study was limited to the Ansan City area. However, participants may be representative of the Korean population because the sampling in Ansan reflects the ratio of the gender and age of the general population.
In conclusion, when adjustments have been made for gender, age, marital status, current job status, monthly income, education duration, diabetes duration, medicine use, current drinking status, current smoking status, regular exercise, obesity, hypertension and HbA1c, comorbid chronic diseases (ordinal multiple logistic regression analysis according to the depression status), vitamin B6, vitamin B2, fiber, and folate, the risk factors of depression among adult diabetic patients were found to be: no occupation, low income, current smoking, oral diabetes medicine or insulin use, and without regular exercise. These results are similar to the findings of other studies.
According to previous studies, diabetes can cause an increase in the level of depression. Also, an increased level of depression promotes neglect of diabetes treatment. Because diabetes is a serious disease requiring lifelong management, avoiding depression is particularly important for people with diabetes [13].
In the future, depression should be recognized as a social problem, and patients should be equipped with a system to actively prevent depression.

This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial-No Derivative Works License (http://creativecommons.org/licenses/by-nc-nd/4.0) which permits non-commercial use, distribution, and reproduction in any medium, provided the original author and source are credited.

  • 1. Office KNS . Causes of death statistics in 2013 [Internet]. 2014, Available from:. http://kosis.kr. [accessed 04.01.15].
  • 2. Welfare MoHa . Korea health statistic 2013 Korea National Health and Nutrition Examination Survey (KNHANES Ⅵ-1) [Internet]. 2014, Available from:. https://knhanes.cdc.go.kr/knhanes. [accessed 17.12.14].
  • 3. Depression CRCf . Guidelines for depression screening in primary care medical [Internet]. 2011, Available from:. http://www.smileagain.or.kr/home/:6. [accessed 22.03.14].
  • 4. Korea Centers for Disease Control and Prevention . Risk factors for depression in older Koreans, community-based geriatric cohort study, 2006–2007. Public Health Wkly Rep 2(44): 2009 Oct;737−741.
  • 5. Park H.-S., Jung M.-H., Yu J.-H.. The relationship between existence of spouses and depression of Korean elderly. J Korea Inst Electron Commun Sci 7(5): 2012 Oct;1181−1187.
  • 6. Niraula K., Kohrt B.A., Flora M.S.. Prevalence of depression and associated risk factors among persons with type-2 diabetes mellitus without a prior psychiatric history: a cross-sectional study in clinical settings in urban Nepal. BMC Psychiatry 13(1): 2013 Nov;1−24. PMID: 23281653.ArticlePubMed
  • 7. Hasan S.S., Mamun A.A., Clavarino A.M.. Incidence and risk of depression associated with diabetes in adults: evidence from longitudinal studies. Community Ment Health J 51(2): 2015 Feb;1−24. PMID: 25344345.ArticlePubMed
  • 8. Sung H.N., Chae H.S., Kim E.S.. Diabetes and depressive symptoms in Korean women: The fifth Korean National Health and Nutrition Examination Survey (2010–2011). Korean J Fam Med 35(3): 2014 May;127−135. PMID: 24921031.ArticlePubMed
  • 9. Roy T., Lloyd C.E.. Epidemiology of depression and diabetes: A systematic review. J Affect Disord 142:2012 Oct;S8−S21. PMID: 23062861.ArticlePubMed
  • 10. Laake J.-P.S., Stahl D., Amiel S.A.. The association between depressive symptoms and systemic inflammation in people with type 2 diabetes: findings from the South London diabetes study. Diabetes Care 37(8): 2014 Aug;2186−2192. PMID: 24842983.ArticlePubMed
  • 11. Hvas A.M., Juul S., Bech P.. Vitamin B6 level is associated with symptoms of depression. Psychother Psychosom 73(6): 2004 Nov–Dec;340−343. PMID: 15479988.Article
  • 12. Tucker K.L.. Vitamin B6 is associated with depressive symptomatology in Massachusetts elders. J Am Coll Nutr 27(3): 2008 Mar;421−427. PMID: 18838531.Article
  • 13. Baik S.-H.. The prevention of diabetes mellitus and the physician's role. Korean J Med 62(5): 2002 Jan;492−496.
  • 14. Ismail K., Winkley K., Stahl D.. A cohort study of people with diabetes and their first foot ulcer: the role of depression on mortality. Diabetes Care 30(6): 2007 Jun;1473−1479. PMID: 17363754.Article
  • 15. Kim H.O., Kim G.N., Park E.. Perception of childhood obesity in mothers of preschool children. Osong Public Health Res Perspect 6(2): 2015 Apr;121−125. PMID: 25938022.Article
  • 16. Yoon H., Yoo S., Kim H.. Composition of metabolic syndrome among Korean adults in a lifestyle modification intervention. Osong Public Health Res Perspect 5(6): 2014 Dec;370−377. PMID: 25562047.Article
  • 17. Yoo S., Kim H., Cho H.I.. Improvements in the metabolic syndrome and stages of change for lifestyle behaviors in Korean older adults. Osong Public Health Res Perspect 3(2): 2012 Jun;85−93. PMID: 24159496.Article
  • 18. Lee J., Keam B., Jang E.J.. Development of a predictive model for type 2 diabetes mellitus using genetic and clinical data. Osong Public Health Res Perspect 2(2): 2011 Sep;75−82. PMID: 24159455.Article
  • 19. Raval A., Dhanaraj E., Bhansali A.. Prevalence and determinants of depression in type 2 diabetes patients in a tertiary care centre. Indian J Med Res 2010 Aug;195−200. PMID: 20716820.
  • 20. Lin E.H.B., Rutter C.M., Katon W.. Depression and advanced complications of diabetes: a prospective cohort study. Diabetes Care 33(2): 2010 Feb;264−269. PMID: 19933989.Article
  • 21. Yu M.K., Weiss N.S., Ding X.. Associations between depressive symptoms and incident ESRD in a diabetic cohort. Clin J Am Soc Nephrol 9(5): 2014 May;920−928. PMID: 24677559.Article
  • 22. Lee W.-B., Lee T.-Y.. A prevalence of anxiety and depression for elderly diabetic patients and the relationship of quality of life. Korean J Fam Pract 3(3): 2013 Jul;323−330.
  • 23. Yoon S.Y., Lim J.H., Han C.. Rating scales for measurement-based clinical practice of depression. J Psychotropic Drugs 23(4): 2012 Jan;136−146.
  • 24. Lee Y., Song J.. A study of the reliability and the validity of the BDI, SDS, and MMPI-D scales. Korean J Clin Psychol 10(1): 1991;98−113.
  • 25. Han J.-K., Lim S.-M.. The effects of brain respiration meditation and cognitive therapy on depressed high school students. Korean J Counsel Psychother 17(4): 2005 Jan;855−876.
  • 26. Lustman P.J., Griffith L.S., Carney R.M.. Screening for depression in diabetes using the Beck Depression Inventory. Psychosom Med 59(1): 1997 Jan/Feb;24−31. PMID: 9021863.Article
  • 27. Park B.-W., Hwang S.Y.. Depression and coping in breast cancer patients. J Breast Cancer 12(3): 2009 Aug;199. Article
  • 28. Shin M.S., Kim Z.S., Park K.B.. The cut-off score for the Korean version of Beck Depression Inventory. Korean J Clin Psychol 12(1): 1993 Jan;71−81.
  • 29. The International Expert Committee . International Expert Committee report on the role of the A1C assay in the diagnosis of diabetes. Diabetes Care 32(7): 2009 Jul;1327−1334. PubMed Central PMCID: PMC2699715. PMID: 19502545.Article
  • 30. American Diabetes Association . Standards of medical care in diabetes—2014. Diabetes Care 37(Suppl. 1): 2014 Jan;S14−80. PMID: 24357209.Article
  • 31. Lee S., Park H.S., Kim S.M.. Cut-off points of waist circumference for defining abdominal obesity in the Korean population. Korean Soc Stud Obes (15): 2006 Jan;1−9.
  • 32. Korean Society for the Study of Obesity . Obesity treatment guidelines 2012 [Internet]. 2012, Available from:. http://www.kosso.or.kr/. [accessed 20.09.14].
  • 33. Al-Amer R.M., Sobeh M.M., Zayed A.A.. Depression among adults with diabetes in Jordan: risk factors and relationship to blood sugar control. J Diabetes Complications 25(4): 2011 Jul;247−252. PMID: 21601482.Article
  • 34. Zahid N., Asghar S., Claussen B.. Depression and diabetes in a rural community in Pakistan. Diabetes Res Clin Pract 79(1): 2008 Jan;124−127. PMID: 17692423.Article
  • 35. Lloyd C.E., Dyert P.H., Barnettt A.H.. Prevalence of symptoms of depression and anxiety in a diabetes clinic population. Diabet Med 17:2000 Jan;198−202. PMID: 10784223.Article
  • 36. Sacco W.P., Bykowski C.A., Mayhew L.L.. Pain and functional impairment as mediators of the link between medical symptoms and depression in type 2 diabetes. Int J Behav Med 20(1): 2011 Dec;22−29. PMID: 22198562.Article
  • 37. Rubin R.T., Poland R.E., Lesser I.M.. Neuroendocrine aspects of primary endogenous depression. I. Cortisol secretory dynamics in patients and matched controls. Arch Gen Psychiatry 44(4): 1987 Jan;328−336. PMID: 3566455.Article
  • 38. Sweileh W.M., Abu-Hadeed H.M., Al-Jabi S.W.. Prevalence of depression among people with type 2 diabetes mellitus: a cross sectional study in Palestine. BMC Public Health 14:2014 Feb;163PMID: 24524353.Article
  • 39. Mitchell A.J., Bird V., Rizzo M.. Diagnostic validity and added value of the Geriatric Depression Scale for depression in primary care: a meta-analysis of GDS 30 and GDS 15. J Affect Disord 125(1): 2010 Sep;10−17. PMID: 19800132.Article
  • 40. Nefs G., Pop V.J., Denollet J.. The longitudinal association between depressive symptoms and initiation of insulin therapy in people with type 2 diabetes in primary care. PLoS One 8(11): 2013 Nov;e78865PubMed Central PMCID: PMC3815321. PMID: 24223860.Article
  • 41. Park Y.S., Lee B.H., Kim J.S.. The Effects of Depressive Symptoms to Metabolic and Glycemic Control among Type 2 Diabetes Patients. J Korean Acad Fam Med. 26(12): 2005 Dec;744−751.
Table 1
General characteristics and the depression prevalence of study participants with Type 2 diabetes mellitus (n = 753).
Characteristics Without depression
Moderate depression
Severe depression
p
16 < BDI, N (%) 16 ≤ BDI < 24, N (%) BDI≥24, N (%)
Overall 536 (71.18) 130 (17.26) 87 (11.55)
Gender
 Male 332 (75.28) 71 (16.10) 38 (08.62) 0.003
 Female 204 (65.38) 59 (18.91) 49 (15.71)
Age (y)
 43–49 171 (73.71) 40 (17.24) 21 (09.05) 0.023
 50–59 209 (75.72) 39 (14.13) 28 (10.14)
 60–73 156 (63.67) 51 (20.82) 38 (15.51)
Marital status
 Married 493 (72.82) 113 (16.69) 71 (10.49) 0.006
 Single/divorced/widowed 43 (56.58) 17 (22.37) 16 (21.05)
Current job status
 Nonphysical labor 178 (82.79) 23 (10.70) 14 (06.51) <0.001
 Physical labor 150 (73.53) 36 (17.65) 18 (08.82)
 No occupation 208 (62.28) 71 (21.26) 55 (16.47)
Monthly income
 ≥1.5 million won 415 (78.01) 75 (14.10) 42 (07.89) <0.001
 <1.5 million won 119 (54.59) 55 (25.23) 44 (20.18)
Education duration (y)
 >9 343 (76.91) 69 (15.47) 34 (07.62) <0.001
 ≤9 193 (62.87) 61 (19.87) 53 (17.26)
Diabetes duration (y)
 ≤1 155 (73.11) 33 (15.57) 24 (11.32) 0.751
 2–5 277 (70.66) 74 (18.88) 41 (10.46)
 6–9 50 (69.44) 11 (15.28) 11 (15.28)
 ≥10 54 (71.05) 11 (14.47) 11 (14.47)
Medicine use
 No 387 (75.73) 78 (15.26) 46 (09.00) <0.001
 Yes 149 (61.57) 52 (21.49) 41 (16.94)
Current drinking 285 (73.83) 64 (16.58) 37 (09.59) 0.161
Current smoking
 No 438 (72.88) 95 (15.81) 68 (11.31) 0.082
 Yes 98 (64.47) 35 (23.03) 19 (12.50)
Regular exercise
 Yes 298 (77.20) 73 (20.05) 54 (14.84) <0.001
 No 237 (65.11) 57 (14.77) 31 (08.03)
Obesity 280 (72.16) 63 (16.24) 45 (11.60) 0.741
Abdominal obesity§ 181 (69.62) 45 (17.31) 34 (13.08) 0.633
Hypertension (yes) 244 (68.73) 66 (18.59) 45 (12.68) 0.371
Comorbid chronic diseases 27 (60.00) 12 (26.67) 6 (13.33) 0.181
Glycated hemoglobin (%)
 <6.5 364 (75.21) 74 (15.29) 46 (09.50) 0.004
 ≥6.5 172 (63.94) 56 (20.82) 41 (15.24)
LDL cholesterol
 <130 330 (71.43) 75 (16.23) 57 (12.34) 0.437
 ≥130 203 (70.73) 55 (19.16) 29 (10.10)
Menstrual status (in women)
 Premenopausal 61 (85.92) 5 (07.04) 5 (07.04) <0.001
 Postmenopausal 143 (59.34) 54 (22.41) 44 (18.26)
Dietary patterns
 Vitamin B6 1.64 ± 0.54 1.63 ± 0.49 1.44 ± 0.63 <0.001
 Vitamin B2 0.98 ± 0.37 0.98 ± 0.42 0.85 ± 0.40 0.001
 Fiber 6.21 ± 2.33 6.10 ± 2.07 5.33 ± 3.13 <0.001
 Folate 224.48 ± 96.06 210.54 ± 80.87 188.53 ± 120.34 <0.001

BDI = Beck Depression Inventory; LDL = low-density lipoprotein.

Chi-square test for categorical variables comparing three-group participants.

Use an oral diabetes medicine or insulin.

Defined as body mass index (calculated as weight in kilograms divided by height in meters squared) of ≥25 kg/m2.

§ Defined as waist circumference (women) ≥85 cm; defined as waist circumference (men) ≥90 cm.

Defined as comorbid chronic diseases (cancer, kidney disease, hyperlipidemia, coronary disease, cerebrovascular diseases).

Values are presented as mean ± standard deviation, Kruskal–Wallis test for continuous variables comparing three-group participants.

Table 2
Unadjusted odds ratios and 95% confidence interval for depression among participants with diabetes (n = 753).
Variable Unadjusted odds ratio (95% confidence interval)
Moderate depression Severe depression
Gender
 Men 1 1
 Women 1.35 (0.92–1.99) 2.10 (1.33–3.32)
Age (y)
 43–49 1 1
 50–59 0.80 (0.49–1.30) 1.09 (0.60–1.99)
 60–73 1.40 (0.88–2.23) 1.98 (1.12–3.53)
Marital status
 Married 1 1
 Single/divorced/widowed 1.73 (0.95–3.14) 2.58 (1.38–4.83)
Current job status
 Nonphysical labor 1 1
 Physical labor 1.86 (1.05–3.27) 1.53 (0.73–3.17)
 No occupation 2.64 (1.59–4.40) 3.36 (1.81–6.25)
Monthly income
 ≥1.5 million won 1 1
 <1.5 million won 2.56 (1.71–3.83) 3.65 (2.29–5.84)
Education duration (y)
 >9 1 1
 ≤9 1.57 (1.07–2.31) 2.77 (1.74–4.41)
Diabetes duration (y)
 ≤1 1 1
 2–5 1.26 (0.80–1.98) 0.96 (0.56–1.64)
 6–9 1.03 (0.49–2.19) 1.42 (0.65–3.11)
 ≥10 0.96 (0.45–2.02) 1.32 (0.60–2.87)
Medicine use
 No 1 1
 Yes 1.73 (1.16–2.58) 2.32 (1.46–3.67)
Current drinking
 No drinking 1 1
 Current drinking 0.85 (0.58–1.25) 0.65 (0.41–1.03)
Current smoking
 No smoking 1 1
 Current smoking 1.25 (0.72–2.17) 1.65 (1.06–2.57)
Regular exercise
 Yes 1 1
 No 1.65 (1.10–2.37) 2.19 (1.36–3.52)
Obesity§
 Normal 1 1
 Abnormal 0.86 (0.59–1.26) 0.98 (0.62–1.54)
Abdominal obesity
 Normal 1 1
 Abnormal 1.05 (0.70–1.57) 1.26 (0.79–2.00)
Hypertension
 No 1 1
 Yes 1.23 (0.84–1.81) 1.28 (0.82–2.02)
Comorbid chronic diseases
 No 1 1
 Yes 1.92 (0.94–3.90) 1.40 (0.56–3.49)
Glycated hemoglobin (%)
 <6.5 1 1
 ≥6.5 1.60 (1.08–2.37) 1.89 (1.19–2.98)
Menstrual status(in women)
 Premenopausal 1 1
 Postmenopausal 4.61 (1.76–12.07) 3.75 (1.42–9.93)
Dietary patterns∗∗
 Vitamin B6 1.09 (0.76–1.55) 0.53 (0.32–0.89)
 Vitamin B2 1.18 (0.71–1.96) 0.46 (0.22–0.93)
 Fiber 1.00 (0.92–1.08) 0.85 (0.76–0.96)
 Folate 1.00 (1.00–1.00) 1.00 (0.99–1.00)

Ordinal logistic analysis according to the depression status compared to nondepression.

Nondepression <16, 16 ≤ moderate depression < 24, severe depression ≥24.

Using an oral diabetes medicine or insulin.

§ Defined as body mass index (calculated as weight in kilograms divided by height in meters squared) of ≥25 kg/m2.

Defined as waist circumference (women) ≥85 cm; defined as waist circumference (men) ≥90 cm.

Defined as comorbid chronic diseases (cancer, kidney disease, hyperlipidemia, coronary disease, cerebrovascular diseases).

∗∗ Adjusted gender, age.

Table 3
Risk factors associated with depression among participants with diabetes (n = 753).
Variable Adjusted odds ratio (95% confidence interval)
Moderate depression Severe depression
Gender
 Men 1 1
 Women 1.25 (0.69–2.26) 1.36 (0.68–2.73)
Age (y)
 43–49 1 1
 50–59 0.80 (0.47–1.36) 0.89 (0.46–1.72)
 60–73 0.84 (0.45–1.55) 0.67 (0.31–1.45)
Marital status
 Married 1 1
 Single/divorced/widowed 0.85 (0.41–1.77) 1.14 (0.53–2.43)
Current job status
 Nonphysical labor 1 1
 Physical labor 1.55 (0.84–2.86) 1.22 (0.56–2.65)
 No occupation 2.31 (1.17–4.54) 1.95 (0.87–4.36)
Monthly income
 ≥1.5 million won 1 1
 <1.5 million won 2.07 (1.23–3.48) 2.46 (1.35–4.46)
Education duration (y)
 >9 1 1
 ≤9 1.04 (0.64–1.69) 1.62 (0.91–2.89)
Diabetes duration (y)
 ≤1 1 1
 2–5 0.89 (0.53–1.49) 0.67 (0.35–1.29)
 6–9 0.46 (0.18–1.18) 0.61 (0.22–1.72)
 ≥10 0.33 (0.12–0.87) 0.42 (0.14–1.24)
Medicine use
 No 1 1
 Yes 2.05 (1.18–3.55) 2.20 (1.13–4.29)
Current drinking
 No drinking 1 1
 Current drinking 0.97 (0.59–1.59) 0.99 (0.551.78)
Current smoking
 No smoking 1 1
 Current smoking 2.40 (1.384.17) 2.46 (1.23–4.90)
Regular exercise
 Yes 1 1
 No 1.46 (0.96–2.23) 1.70 (1.02–2.82)
Obesity§
 Normal 1 1
 Abnormal 0.77 (0.50–1.19) 0.89 (0.53–1.48)
Abdominal obesity
 Normal 1 1
 Abnormal 0.98 (0.57–1.70) 1.01 (0.52–1.99)
Hypertension
 No 1 1
 Yes 1.15 (0.74–1.78) 1.05 (0.63–1.77)
Comorbid chronic diseases
 No 1 1
 Yes 1.50 (0.68–3.29) 0.88 (0.30–2.53)
Glycated hemoglobin (%)
 <6.5 1 1
 ≥6.5 1.38 (0.84–2.27) 1.68 (0.93–3.01)
Dietary patterns
 Vitamin B6 1.85 (0.64–5.39) 1.04 (0.28–3.92)
 Vitamin B2 1.90 (0.74–4.89) 1.11 (0.32–3.83)
 Fiber 1.13 (0.91–1.42) 0.89 (0.67–1.19)
 Folate 0.99 (0.99–1.00) 1.00 (0.99–1.01)

Ordinal logistic analysis according to the depression status compared to nondepression. Adjustment for gender, age, marital status, current job status, monthly income, education duration, diabetes duration, medicine use, current drinking, current smoking, regular exercise, obesity, hypertension and glycated hemoglobin, comorbid chronic diseases (ordinal multivariate analysis according to the depression status), vitamin B6, vitamin B2, fiber, and folate.

Nondepression <16, 16 ≤ moderate depression < 24, severe depression ≥24.

Using an oral diabetes medicine or insulin.

§ Defined as body mass index (calculated as weight in kilograms divided by height in meters squared) of ≥25 kg/m2.

Defined as waist circumference (women) ≥ 85 cm; defined as waist circumference (men) ≥ 90 cm.

Defined as comorbid chronic diseases (cancer, kidney disease, hyperlipidemia, coronary disease, cerebrovascular diseases).

Figure & Data

References

    Citations

    Citations to this article as recorded by  
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      Iranian Journal of Pediatrics.2020;[Epub]     CrossRef
    • Prevalence of Undiagnosed Depression in Patients With Type 2 Diabetes
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      Frontiers in Endocrinology.2019;[Epub]     CrossRef
    • Risk and protective factors of co-morbid depression in patients with type 2 diabetes mellitus: a meta analysis
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      Acta Diabetologica.2019; 56(6): 631.     CrossRef
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      PLOS ONE.2018; 13(6): e0198915.     CrossRef
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      Diabetes & Metabolism Journal.2018; 42(2): 93.     CrossRef
    • Why Early Psychological Attention for Type 2 Diabetics Could Contribute to Metabolic Control
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      Romanian Journal of Diabetes Nutrition and Metabol.2018; 25(3): 329.     CrossRef
    • Depression and Mortality in People with Type 2 Diabetes Mellitus, 2003 to 2013: A Nationwide Population-Based Cohort Study
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      Diabetes & Metabolism Journal.2017; 41(4): 296.     CrossRef
    • Diabetes-related distress and its associated factors among patients with type 2 diabetes mellitus in China
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