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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 



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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) 



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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.



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Type	of	psychosocial	stressor	as	risk	factor	of	depressive	symptom	in	metabolic	syndrome	

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