262 Bangladesh Journal of Medical Science Vol. 15 No. 02 April’16 Original article Type of psychosocial stressor as risk factor of depressive symptom in metabolic syndrome Fauziyati A1, Siswanto A2, Purnomo LB3, Sinorita H3 Abstract: Metabolic syndrome and depression are two major diseases over the world, which are increasing in prevalence over time. Depression is a major mental health burden over the world. In long time, depression can lead to metabolic syndrome, while metabolic syndrome is a risk factor for developing depression. Metabolic syndrome is a major risk factor for developing cardiovascular disease. Chronic stress induced by psychosocial stressor leads to the development of both metabolic syndrome and depression. Further research is important to identify which type of psychosocial stressor is the risk factor for depressive symptom in patients with metabolic syndrome. The objective of this study is to identify the type of psychosocial stressor which could be the risk factor for depressive symptom. The study design was case control. The case group consisted of metabolic syndrome patients with depressive symptom, while the control group consisted of metabolic syndrome patients without depressive symptom. Metabolic syndrome was diagnosed based on International Diabetes Federation (IDF) criteria. Depressive symptom was measured by Beck Depression Inventory (BDI). Psychosocial stressors were measured by Stressful Life Events (SLE) questionnaire. Dependent variable was depressive symptom, while independent variables were type of psychosocial stressors (finance, work, social relationship, health and housing). Analysis methods that used in this study were independent t test, Pearson/ Spearman correlation analysis, chi square and logistic regression. There were 54 patients in this study, consisted of 24 in case group and 30 in control group. There was no significant difference in most basic characteristics between two groups. There was significant difference of SLE score between two groups. Chi square analysis showed that housing, finance, health, social relationship, and work stressors were risk factors for developing depressive symptom in metabolic syndrome (OR 24.5 (p 0.001); 9.7 (p 0.039); 8.4 (p 0.016); 5.4 (p 0.004); 3.9 (p 0.001), respectively). Demographic factor which also influenced depressive symptom was salary less than 1 million per month (OR 45, p 0.004). According to logistic regression analysis, psychosocial stressors which most influenced the depressive symptom were finance and housing. In conclusion, this study showed that housing, finance, health, social relationship and work stressors were risk factors for developing depressive symptom in metabolic syndrome. Keywords: psychosocial stressor; metabolic syndrome; depression Corresponds to: Ana Fauziyati, Internal Medicine Department, Faculty of Medicine, Universitas Islam Indonesia, Jalan Kaliurang km 14,5, Yogyakarta, Indonesia. E-mail: afauziyati@yahoo.com 1. Internal Medicine Department, Faculty of Medicine, Universitas Islam Indonesia 2. Sub Division of Psychosomatic, Internal Medicine Department, Faculty of Medicine, Gadjah Mada University 3. Sub Division of Endocrine, Metabolic and Diabetes, Internal Medicine Department, Faculty of Medicine, Gadjah Mada University Bangladesh Journal of Medical Science Vol. 15 No. 02 April’16. Page : 262-268 Introduction Metabolic syndrome and depression are two major diseases which are increasing over time because of sedentary lifestyle, including high calory intake and poor physical activity1. About 15% population ever had major depression episode in their life and 263 Type of psychosocial stressor as risk factor of depressive symptom in metabolic syndrome Note: *significant; Education 1: no education andelementary school, 2: junior and senior high school, bachelor, 3: graduate and post graduate; Occupation 1: Unemployed,house wife, 2: Private, labor, farmer 3: government employment, retired, army, policeman,Income 1:<1 million/month, 2:1-5 million/month, 3:>5 million/month, Marital Status 1: Never married, 2: married, 3: divorce/death spouse Table 1. Baseline Characteristic between Case Group and Control Group Characteristic (mean) Case Group (n=24) Control Group (n=30) Significance (p) Age (year) 51,29 52,05 0,771 Duration of DM (month) 52,67 40,83 0,356 Body Mass Index (kg/m2) 25,87 27,10 0,37 Waist Circumference (cm) 90,42 94,95 0,124 Systolic Blood Pressure (mm Hg) 134,3 135,5 0,821 Diastolic Blood Pressure (mm Hg) 78,38 78,6 0,52 Fasting Glucose (mg/dL) 187 154 0,196 Post Prandial Glucose (mg/dL) 304 208 0,02* HbA1C (%) 9,8 8,2 0,095 Trygliserid (mg/dL) 160 188 0,3 HDL Cholesterol (mg/dL) 40,5 46 0,15 LDL Cholesterol(mg/dL) 132 131 0,978 Total Cholesterol (mg/dL) 199 196 0,882 BUN (mg/dL) 17,4 16,9 0,679 Creatinin (mg/dL) 1,30 1,16 0,799 Uric Acid (mg/dL) 6,5 6,0 0,552 SGOT (U/L) 33 22 0,319 SGPT (U/L) 85 22 0,35 Demographic Factor n (proportion %) OR (95% CI) P Education 1 4 (0,17) 3 (0,1) 4,0 (0,55-29,17) p 0,171 2 17 (0,78) 18 (0,6) 2,83 (0,6-1,2) p 0,164 3 3 (0,12) 9 (0,3) Referee Occupation1 5 (0,21) 9 (0,3) 0,9 (0,2-4,0) p 0,947 2 12 (0,5) 9 (0,3) 2,28 (0,64-8,15) p 0,202 3 7 (0,29) 12 (0,4) Referee Income 1 9 (0,38) 2 (0,07) 45,0 (3,4-584) p 0,004* 2 14 (0,59) 18 (0.6) 7,78 (0,88-68) p 0.064 3 1 (0,42) 10 (0,33) Referee Sex Female 13 (54,2) 16 (53,3) 0,97 (0,33-2,84) p 0,951 Male 11 (45,8) 14 (46,7) Marital Status1 1 (0,042) 2 (0,07) 0,66 (0,05-7,0) p 0,74 2 4 (0,17) 3 (0,1) 1,75 (0,35-8,79) p 0,494 19 (0,79) 25 (0,83) Referee Complication Retinopathy Yes 5 (20,8) 7 (23,3) 0,86 (0,24-3,17) p 0,826 No 19 (79,2) 23 (76,7) Nephropathy Yes 5 (20,8) 5 (16,7) 1,32 (0,33-5,21) p 0,695 No 19 (79,72) 25 (83,3) Neuropathy Yes 10 (41,7) 8 (26,7) 1,96 (0,62-6,17) p 0,245 No 14 (58,3) 22 (73,3) Peripheral Artery DiseaseYes 0 (0) 4 (13,3) 0,52 (0,39-0,68) p 0,063 No 24 (100) 26 (86,7) Coronary Artery Disease Yes 3 (12,5) 5 (16,7) 0,71 (0,15-3,35) p 0,688 No 21 (87,5) 25 (83,3) Stroke Yes 0 (0) 1(3,3) 0,55(0,43-0,70) p 0,367 No 24 (100) 29 (96,7) 264 Fauziyati A, Siswanto A, Purnomo LB, Sinorita H Table 2. Correlation between Metabolic Syndrome Component and Depressive Symptom Table 3. Comparison of Stressful Life Events (SLE) Score between Case and Control Group Note: *significant Metabolic Syndrome Component Classi fication Control Group Case Group Significance (p) Waist Circumference 0 4 6 0,273 1 26 18 Systolic Blood Pressure 0 14 13 0,584 1 16 11 Diastolic Blood Pressure 0 21 18 0,684 1 9 6 Fasting Glucose 0 5 2 0,318 1 22 21 Trygliserid 0 15 11 0,49 1 11 12 HDL Cholesterol 0 15 9 0,149 1 10 14 Total of metabolic syndrome component ≤3 22 14 0,245 >3 8 10 SLE Score (mean) Case Group Control Group Significance(p) SLE total score 12,2 4,63 0,001* Finance 3,88 1,00 0,001* Work 1,21 0,7 0,165 Social Relationship 1,04 0,33 0,023* Health 4,92 2,2 0,001* Housing 1,67 0,33 0,004* Note: * significant Table 4. Correlation between SLE Score and BDI Score Dependent Variable Independent variable Pearson/Spearman Correlation (r) Significance (p) BDI Score SLE total score 0,688 0,001* Finance 0,308 0,076 Work 0,171 0,423 Social Relationship 0,643 0,007* Health 0,384 0,01* Housing 0,480 0,032* about 6-8% out patients in primary health care met the criteria of depression. Depression was often undiagnosed2. Depression makes the treatment of metabolic syndrome complicated. Some studies showed depression made the glucose control difficult in patient with metabolic syndrome and diabetes mellitus3,4,5. Depression decreased quality of life 6,7. Depression increased the risk of metabolic syndrome and cardiovascular disease8. In the other hand, metabolic syndrome also increased the risk of depression9,10. The relationship between metabolic syndrome and depression is bidirectional 10,11,12,13,14,15. There are some studies which could not find the relationship between depression and metabolic syndrome16,17,18. Psychosocial stressor in long time lead to depression. Type of psychosocial stressor include marital status, family problems, interpersonal relationship, work problem, environtment, law, finance and health19. Study showed subject with chronic life stressor especially work and finance had higher risk for developing metabolic syndrome20. Psychosocial stressor and chronic stress increased the activity of hypothalamus- pituitary-adrenal which increased cortisol level in blood, which in long time caused the insulin resistance or metabolic syndrome through central obesity21,22. Hypercortisolism induced the neurobiology imbalance in amigdala and frontal cortex that manifested in emotional disorder, mood and depression23. Psychosocial stressors which are not adapted well will induce the depressive symptomp19. Problem in this study is what kind of psychosocial stressor which can be risk factor for developing depressive symptomp in metabolic syndrome. Method Design of the study is case control. Case group consist of patients with metabolic syndrome who have depressive symptom, while control group consist of patients without 265 Type of psychosocial stressor as risk factor of depressive symptom in metabolic syndrome Type of Psychosocial Stressor Depressive Symptom (+) No Depressive Symptom Odds Ratio (OR) CI 95% Significance p Finance No 24 7 9,714* 2,7-34,07 0,001* Yes 6 17 Work No 26 15 3,9* 1,02- 14,86 0,039* Yes 4 9 Social Relationship No 27 15 5,4* 1,26- 23,04 0,016* Yes 3 9 Health No 13 2 8,4* 1,67- 42,41 0,004* Yes 17 22 Housing No 29 13 24,5* 2,8-210 0,001* Yes 1 11 Table 5. Chi SquareAnalysis of Type of Psychosocial Stressors as Risk Factor for Developing Depressive Symptom in Metabolic Syndrome Table 6. Logistic Regression of Type of Psychosocial Stressor as Risk Factor for Developing Depressive Symptom in Metabolic Syndrome Step Variable Coefficient p OR (CI 95%) Step 1 Finance 3,277 0,138 0,689-15,732 Work 1,800 0,500 0,326-9,915 Social Relationship 3,196 0,235 0,47-21,755 Health 3,241 0,247 0,443-23,712 Housing 13,304 0,037* 1,17-151,296 Constant 0,088 0,050 Step 2 Finance 3,474 0,160 0,735-16,42 Social Relationship 3,400 0,196 0,525-23,148 Health 3,579 0,206 0,495-25,870 Housing 13,602 0,034* 1,223-152,394 Constant 0,089 0,050 Step 3 Finance 3,535 0,105 0,769-16,238 Health 3,498 0,214 0,485-25,209 Housing 14,952 0,022* 1,468-152,267 Constant 0,109 0,009* Step 4 Finance 5,876 0,011* 1,500-23,017 Housing 13,420 0,023* 1,423-126,578 Constant 0,233 0,020* depressive symptom. The study was conducted at Dr Sardjito Central Hospital, from July 2014 until the minimum sample of subject achieved. Subjects of the study are achieved from the population who meet the inclusion criteria and do not have exclusion criteria. Inclusion criteria for case group are: age ≥18 and ≤60 years old, signed informed consent and have depressive symptom with Beck Depression Inventory (BDI) score ≥ 14. Inclusion criteria for control group are: age ≥18 and ≤ 60 years old, signed informed consent and do not have depressive symptom (score of BDI <14). Exclusion criteria are: psychotic mental disorder, end stage of renal disease, congestive heart failure class functional IV, acute myocardial infarct, stroke or post stroke, diabetic ulcer, diabetes mellitus more than 10 years, using psychotropic agent, active smoker, alcoholic, and pregnant woman. The measurement of sample size is based on case control design24. Characteristic of study subject is presented in mean. Distribution of data was detected by normality test. To analyze the difference of mean between two groups we used t test. To determine the relationship between psychosocial stressor and depressive symptom we used chi square. To determine which psychosocial stressor to be the risk of depressive symptom in metabolic syndrome 266 Fauziyati A, Siswanto A, Purnomo LB, Sinorita H patient, we used multivariate analysis using logistic regression. During the study, patients who meet the inclusion and exclusion criteria are asked about their history and psychosocial stressor, fulfill the Beck Depression Inventory and the Stressful Life Event Inventory. Physical examination is conducted to all patients, especially to measure height, weight, blood pressure, and waist circumference. All the study subjects signed their informed consent to joint this study. This study was approved by Ethics Committee of Faculty of Medicine, Gadjah Mada University and had license from Director of Dr. Sardjito Central Hospital. Result There were 54 patients, consisted of 24 in case group, and 30 in control group. Table 1 showed no differences of age, duration of diabetes mellitus, body mass index, waist circumference, systolic and diastolic blood pressure, fasting glucose, HbA1c, trygliserid, high density lipoprotein cholesterol, low density lipoprotein cholesterol, total cholesterol, blood urea nitrogen, creatinin, SGOT, SGPT, and uric acid between two groups. There was significant difference in post prandial glucose between two groups (304 vs. 208, p = 0.02). There was no difference between proportions of demographic factors between two groups, except income. Patient with income less than 1 million per month had higher risk for developing depression than patient with income more than 5 million per month (OR 45, CI 95% 3.4-584). Proportion of complication such as retinopathy, nephropathy, neuropathy, peripheral artery disease, coronary heart disease, and were not different between two groups. Chi square analysis showed no correlation between metabolic syndrome component and total of metabolic syndrome component with depressive symptom (table 2). There was significant difference of SLE total score, score of finance, social relationship, health and housing between two groups (table 3). Pearson and Spearman correlation test showed that there were positive correlations between Beck Depression Inventory score with SLE total score (r = 0,688, p < 0,001), social relationship (r = 0,643, p = 0,007), health (r = 0,384, p = 0,01) and housing (r = 0,480, p = 0,032) (table 4). Table 5 showed the high and significant Odds Ratio (OR) of all stressors, with the highest was housing (OR 24.5), followed by finance (OR 9.714), health (OR 8.4), social relationship (OR 5.4), and work (OR 3.9). Logistic regression showed that the most influencing factors for developing depressive symptom were housing and finance (table 6). Discussion This study compared 24 patients in case group and 30 patients in control group. There was difference of post prandial glucose between two groups, that was significant higher in case groups (304 vs. 208, p=0.02). This is relevant with previous study which stated depression complicate blood glucose control in metabolic syndrome or diabetes patient3,4,5,25,26. There was no correlation between metabolic syndrome component and depression. This result was different with previous study27,28. There was no difference of complication propotion between two groups, that is good to minimalize bias. Income was correlated with depreesive symptom. This was relevant with previous study that stated low social economic level correlated with mental disorder in obese women29. There was significant difference of type of psychosocial stressor between two groups. This evidence supported that psychosocial stressor influenced the developing of depression in metabolic syndrome23. Correlation test also showed the moderate and high correlation between SLE total score, social relationship, health and housing with BDI score. Chi square analysis showed that housing, finance, health, social relationship and work stressors were the risk factors for developing depressive symptom in metabolic syndrome. This result was relevant with previous study that stated people with finance and work stressors had higher risk for developing metabolic syndrome20. This result was different with previous study that stated there was no correlation between psychological distress and metabolic syndrome30. Logistic regression showed that housing and finance stressors were the highest risk factors for developing depressive symptom in metabolic syndrome. This was relevant with previous study20. Conclusion Type of psychosocial stressors which defined as the risk factors for developing depressive symptom in metabolic syndrome were housing, finance, health, social relationship and work. 267 Type of psychosocial stressor as risk factor of depressive symptom in metabolic syndrome 1. Eckel, R.H., 2008. The metabolic syndrome. Chapter 236:1509-1513, in: Fauci, A.S., Braunwald, E., Kasper, D.L., Hauser, S.L., Longo, D.L., Jameson, J.L., Loscalzo, J. (Eds.). Harrison’s Principles of Internal Medicine, 17th ed., McGraw Hill Medical, New York. 2. Reus, V.I., 2008. Mental disorders. Chapter 386:2710- 2723, in: Fauci, A.S., Braunwald, E., Kasper, D.L., Hauser, S.L., Longo, D.L., Jameson, J.L., Loscalzo, J. (eds.), 2008. Harrison’s Principles of Internal Medicine, 17th ed., McGraw Hill Medical, New York. 3. Zuberi, S.I., Syed, E.U., Bhatti, J.A., 2011. Association of depression with treatment outcomes in type 2 diabetes mellitus: a cross sectional study from Karachi, Pakistan. BMC Psychiatry, 11(27):1-6. 4. Pouwer, F. & Snoek, F.J., 2001. Association between symptoms of depression and the glycaemic control may be unstable across gender. Diabetic Medicine, 18:595- 598. 5. Zihl, J., Schaaf, L., Ziler, E.A., 2010. The relationship between adult neurophysiological profiles and diabetic patient’s glycemic control. Applied Neurophysiology, 17:44-51. 6. Eren, I., Erdi, O., Sahin, M., 2008. The effect of depression on quality of life of patients with type II diabetes mellitus. Depression and Anxiety, 25; 98-106. 7. Hyvarinen, M.P., Wahlbeck, K., Erickson, J.G., 2007. Quality of life and metabolic status in mildly depressed patients with type 2 diabetes treated with paroxetine: a double-blind randomized controlled 6-month trial. BMC Family Practice, 8(34):1-7. 8. Vanhala, M, Jokelainen, J., Kiukaanniemi, K., S., Kumpuasalo, E., Koponen, H., 2009. Depressive symptoms predispose females to metabolic syndrome: a 7 year follow up study. Acta Psychiatrica Scandinavica, 119:137-142. 9. Dortland, R.A.K.B., Giltay, E.J., Veen, T., Zitman, F.G., Penninx, B.W.J.H., 2010. Metabolic syndrome abnormalities are associated with severity of anxiety and depression and with tricyclic antidepressant use. Acta Psychiatrica Scandinavica, 122:30-39. 10. Akbaraly, T.N., Ancelin, M.L., Jaussent, I., Ritchie, C., Gateau, P.B., et al., 2011. Metabolic syndrome and onset of depressive symptoms in the elderly findings from the three city study. Diabetes Care, 34:904-909. 11. Toker, S., Shirom, A., Melamed, S., 2008. Depression and the metabolic syndrome: gender dependent associations. Depression and Anxiety, 25:661-669. 12. Heiskanen T., Viinamaki, H., Lehto, S.M., Niskanen, L., Honkanen, K., et al., 2009. Association of depressive symptoms and the metabolic syndrome in men. Acta Psychiatrica Scandinavica, 120:23-29. 13. Akbaraly, T.N., Kivimaki, M., Brunner, E.J., Chandola, T., Marmot, M.G., et al., 2009. Association between metabolic syndrome and depressive symptoms in middle-aged adults results from the Whitehall II study. Diabetes Care, 32(3):499-504. 14. Hartley, T.A., Knox, S.S., Fekedulegn, D., Leiker, C.B., Violanti, J.M., et al., 2012. Association between depressive symptoms and metabolic syndrome in police officers: results from two cross sectional studies. Journal of Environmental and Public Health, 1-9. 15. Meittola, J., Niskanen, L.K., Vinamaki, H., Kumpusalo, E., 2008. Metabolic syndrome is associated with self perceived depression. Scandinavian Journal of Primary Health Care, 26:203-210. 16. Demirci, H., Cinar, Y., Bilgel, N., 2011. Metabolic syndrome and depressive symptoms in a primary health care setting in Turkey. Bulletin of Clinical Psychopharmacology, 21(1):49-57. 17. Hildrum, B., Mykletun, A., Midthjell, K., Ismail, K., Dahl, A.A., 2009. No association of depression and anxiety with the metabolic syndrome: the Norwegian HUNT study. Acta Psychiatrica Scandinavica, 120:14- 22. 18. Foley, D.L., Morley, K.I., Madden, P.A.F., Heath, A.C., Whitfield, J.B., Martin, N.G., 2010. Major depression and the metabolic syndrome. Twin Research and Human Genetics, 13(4):347-358. 19. Mudjaddid, E. & Shatri, H., 2009. Gangguan psikosomatik: gambaran umum dan patofisiologinya, in: Sudoyo, A.W., Setiyohadi, B., Alwi, I., Simadibrata, M.K., Setisti, S. (editor). Buku Ajar Ilmu Penyakit Dalam. jilid III, edisi V., page: 2093-2097. Interna Publishing, Jakarta. 20. Pyykkonen, A.J., Raikkonen, K., Tuomi, T., Erickson, J.G., Groop, L., Isomaa, B., 2010. Stressful life events and the metabolic syndrome. Diabetes Care, 33(2): 378-384. 21. Bjontorp, P., 2001. Do stress reaction cause abdominal obesity and comorbidities?. Obesity Reviews, 2:73-86. 22. Vogelzangs, N., 2010. Depression & Metabolic Syndrome. Dissertation. Universiteit Amsterdam. 23. Sharpley, C.F., 2009. Neurobiological pathway between chronic stress and depression: dysregulated Reference: 268 Fauziyati A, Siswanto A, Purnomo LB, Sinorita H adaptive mechanisms?. Clinical Medicine: Psychiatry 2:39-45. 24. Dahlan, M.S., 2010. Besar Sampel dan Cara Pengambilan Sampel dalam Penelitian Kedokteran dan Kesehatan, ed. 3:46-60. Salemba Medika Publisher, Jakarta. 25. Toker, S., Shirom, A., Melamed, S., 2008. Depression and the metabolic syndrome: gender dependent associations. Depression and Anxiety, 25:661-669. 26. Lloyd, C.E., Dyert, P.H. dan Barnett, A.H., 2000. Prevalence of symptoms of depression and anxiety in a diabetes clinic population. Diabetic Medicine, 17:198- 202. 27. Dunbar, J.A., Reddy, P., Lameloise, N.D., Philpot, B., Laatikanen, T., Kilkkinen, A., et al., 2008, Depression: an important comorbidity with metabolic syndrome in a general population, Diabetes Care 31: 2368-2373. 28. Kinder, L.S., Carnethon, M.R., Palaniappan, L.P., King, A.C., Fortmann, S.P., 2004. Depression and the metabolic syndrome in young adults: findings from the Third National Health and Nutrition Examination Survey. Psychosom Med 66:316 –322. 29. Gatineau, M. & Dent, M. 2011. Obesity and Mental Health. Oxford: National Obesity Observatory, pp:1- 28. 30. Herva, A., Rasanen, P., Miettunen, J., Timonen, M., Laksy, K., Veijola, J., Laitinen, J., Ruokonen, A., Joukamaa, M, 2004. Co-occurrence of metabolic syndrome with depression and anxiety in young adults: the Northern Finland 1966 Birth Cohort Study. Psychosom Med 68:213–216.