« Go back to issue 48(1) summary

The Impact of Visceral Adipose Tissue on the Severity of Anxiety and Depression

Sengul Kocamer Sahin1, Bahadır Demir1, Gülcin Elboga1, Abdurrahman Altındağ1, Ünzile Meryem Atalay1, Ayşegül Şahin Ekici1

1 Gaziantep University, Faculty of Medicine, Department of Psychiatry, Gaziantep, Turkey

 

Received: 02/05/2020 – Accepted: 01/10/2020

DOI: 10.15761/0101-60830000000269

Abstract

Background: There is a reciprocal relationship between psychopathologies and visceral adiposity. A few studies reviewed the relationship between visceral adiposity and major depressive disorder (MDD) and/or particularly anxiety disorders (ADs). Objective: This study aimed to investigate the relationship between dysfunctional visceral adipose tissue (VAT) and severity of anxiety/depression in two patient groups diagnosed with MDDs and ADs that are non-responders to antidepressants. Methods: The Hamilton Depression Rating Scale (HDRS) and the Hamilton Anxiety Rating Scale (HARS) were used for the assessment. This cross-sectional study included 89 patients, of which 44.9% had MDD, and 55.1% had ADs and 40 healthy individuals as control group. VAT was calculated using the visceral adiposity index (VAI) formula. Results: Although VAI was significantly higher in patients with MDD than control group (p=0.008), there was no difference between patients with ADs and the control group (p=0.072). There was a positive correlation between VAI and HDRS in patients with MDD (P = 0.034 r: 0.336), while there was no significant correlation between VAI and HARS in patients with ADs. Multiple regression analysis revealed significant associations between HDRS and VAI after adjusting for age, gender, and educational levels (P = 0.042). Conclusion: This study suggests that VAT, which may have an important role in the physiopathology and severity of depression in patients with MDD, may not play a similar role in the physiopathology and severity of anxiety in patients with ADs.

Sahin SK / Arch Clin Psychiatry. 2021;48(1):01-05

Keywords

Visceral adiposity, anxiety, depression

Introduction

Major depressive disorder (MDD) and anxiety disorders (ADs) and are the most prevalent psychiatric disorders associated with a high burden of disease. ADs are classified as panic disorder, agoraphobia, generalized AD, social AD, selective mutism, specific phobias, and separation AD, according to the DSM-51. In patients with any of the ADs, anxiety is excessive and unreasonable and also disproportionate to the real danger posed by the situation (1). MDD is defined as the presence of five of the following criteria: not enjoying life for a period of at least two weeks, depression, fatigue, psychomotor retardation, changes in sleep patterns and appetite, thoughts of self-worthlessness, distraction, and suicidal thoughts according to the DSM-52.

Increased visceral adipose tissue (VAT) is a risk indicator for cardiovascular diseases, metabolic disorders, malignancy, and visceral adipose dysfunction (VAD) that appears to be associated with cardiometabolic risks3-5. The visceral adiposity index (VAI), which is calculated using the waist circumference, body mass index (BMI), and lipid values for VAT analysis, is developed to calculate the dysfunctional VAT of an individual and was found to be significant in the risk assessment for cardiovascular diseases3-5. This scale can be considered as a simple VAD indicator that assesses cardiometabolic risk. VAT may also be increased in patients with normal weight; therefore, it may help with early diagnosis and could protect the patient with regard to the metabolic syndrome that is considered as the cause of obesity6.

VAT secretes cytokines and adipokines and creates a pro-inflammatory condition in obesity7,8. Some of these secreted factors are also considered as potential factors for some mental disorders8. For example, inflammatory genes in the VAT were found to be significantly higher in patients with anxiety or mood disorders than in subjects without mental disorders9. Although there have been numerous studies about the relationship between increased visceral adiposity and schizophrenia and/or mood disorder10,11, there are few studies that reviewed the relationship between visceral adiposity and major depression and/or particularly Ads12,13; however, the reciprocal relationship between these psychopathologies and visceral adiposity is not fully understood. In the general population, overall and abdominal adiposity measurements were found to be associated with a depressive mood14 Increased BMI was speculated to lead to anxiety, which is found to be more frequently in obese/overweight people15. Another issue is the lack of response to treatments for depression and/or anxiety in overweight patients. Studies confirmed the significance of body weight and BMI in treating MDD16. For example; a study found that a greater body weight without obesity predicted the lack of response to fluoxetine which is selective serotonin reuptake inhibitor17. So, increased visceral adiposity may be a reason for this unresponsiveness.

This study aims to analyze 1) VAI in patients with MDD and ADs and 2) the relationship between anxiety/depression and VAI in two groups of patients with MDDs and ADs who are non-responders to SSRI/SNRI to determine if high VAI is associated with non-response to treatment in MDDs and/or ADs.

Methods

In this study, we compared three groups; patients with ADs, patients with MDD, and healthy individuals. We compared the difference between groups in terms of dysfunctional visceral adipose tissue using VAI. We also examined the relationships between the severity of depression and VAI in patients with MDD and between the severity of anxiety and VAI in patients with ADs.

Study population

Patients admitted to the psychiatry outpatient clinic at the Gaziantep University Faculty of Medicine, Gaziantep, Turkey diagnosed with MDD or ADs according to the DMS 5 were included in this cross-sectional study. The diagnosis for MDD and ADs was made by two psychiatrists. Of the 89 patients, 44.9% had MDD, and 55.1% had ADs. Of the 49 patients with ADs, 24 had generalized AD, six had panic disorder, four had social AD, and 15 had unspecified AD. Of the 40 patients with MDD, 40% were males, 65% were married, and their mean age was 43.4 ± 14.5. Of the 49 patients with ADs, 20.4% were males, 77.6% were married, and their mean age was 36.1 ± 13.2 (Table 1). The control group was selected from a total of 40 healthy individuals who came to the hospital for general screening after applying to the Health Commission to get a clean bill of health in the preceding 6 months and who were found to have no disabilities.

The study was approved by the Clinical Trials Ethics Committee of Gaziantep University. All participants filled out a written consent form. Non-response is described as a less than 50% improvement in the total score of a commonly used anxiety rating scale or a non-response to an adequate dose of first-line pharmacological Selective serotonin reuptake inhibitor SSRI/ serotonin noradrenalin reuptake inhibitors (SNRI) treatment for 4–6 weeks, compatible with previous studies18.

Procedure

In this study, we compared three groups; patients with ADs, patients with MDD, and healthy individuals. We compared the difference between groups in terms of dysfunctional visceral adipose tissue using VAI. We also examined the relationships between the severity of depression and VAI in patients with MDD and between the severity of anxiety and VAI in patients with ADs.

The metabolic parameters of the patients were monitored every six months in the outpatient clinic for anxiety and mood disorders. After determining the patients, the required new parameters and results were recorded for 6 months. Patients with severe neurological diseases, diabetes mellitus, and other endocrinopathies, liver disease, malignant diseases, mental retardation, alcohol, substance use disorder, or a history of addiction were not included in the study. Anxious depressions were also excluded so that the results are not affected. In addition, we used the Hamilton Depression Rating Scale (HDRS) and the Hamilton Anxiety Rating Scale (HARS) in both patient groups. We excluded patients with an anxiety score above 7 for the MDD group and those with a depression score above 7 for the ADs group. The sociodemographic data of all patients, such as age and gender, were recorded.

Assessment Tools

Visceral Adiposity Index (VAI)

The heights and weights of each subject were measured using the same calibrated weight scale with bare feet and light clothing. The waist circumference of subjects was measured at the middle level between the inferior costal margin and the upper iliac crest while they were standing. Peripheral venous blood samples were obtained after 12 hours of fasting, and the blood samples were analyzed on the same day. High-density lipoprotein (HDL) and triglyceride (TG) were analyzed using the spectrophotometric method on a Beckman device.

The VAI of female patients was calculated with the Waist circumference / [36.58 + (1.89 x BMI)] x (TG / 0.81) x (1.52 / HDL) formula, while the Waist circumference / [39.68 + (1.88 x BMI)] x (TG / 1.03) x (1.31 / HDL) formula was used in male patients3,5.

Hamilton Depression Ratind Scale (HDRS)

The HDRS, developed by Hamilton in 1960, measures the level and severity of depression in the patient19. It consists of 21 items. Items on the HDRS scale are marked between 0–4 and 0–2. The Turkish validity and reliability study was done by Akdemir et al. in 199620.

Hamilton Anxiety Rating Scale (HARS)

This is a rating scale developed to measure the severity of anxiety symptoms. It was developed by Hamilton to determine the level of anxiety and symptom distribution in individuals21. The Turkish validity and reliability study was performed by Yazıcı et al22.

Statistical Analysis

Descriptive statistics were used to evaluate the demographic characteristics with the data acquired from the 49 patients with MDD and 40 patients with ADs. The Chi-square test was used in the comparison of categorical variables. Kruskal–Wallis followed by post hoc tests uses to compare groups. Multiple regression analysis was performed to correct the effect of age, gender, and education on the severity of anxiety/depression. Windows version of SPSS 22.0 package software was used in the analyses. P < 0.05 was considered as significant.

Results

There were no significant differences between groups in terms of age, sex, marital status and education. Patients’ sociodemographic data is shown in table 1. The most used drug in both patient groups was Sertraline followed by paroxetine, fluoxetine and others. Table 2 shows the distribution of drugs that patients in both groups used.

Table 1: Sociodemographic data of Patients

 

MAJOR DEPRESSIVE DISORDER

ANXIETY DISORDERS

CONTROL

P

Sex

Male

16 (40%)

10 (20.4%)

13(20.4%)

0.12

Female

24 (60%)

39 (79.6%)

27 (67%)

Age

 

43.4±14.5

36.1±13.2

37.1±0.89

0.051

Education (years)

 

8.9±3.2

9.4±3.3

9.49±2.3

0.78

Marital Status

Single

14 (%35)

11 (%22.4)

7(17%)

0.84

Married

  26 (%65)

  38 (%77.6)

33(83%)

Table 2: Pharmacotherapy data of patients

MAJOR DEPRESSIVE DISORDER

ANXIETY DISORDERS

Frequency

Percent

Frequency

Percent

Valid

Fluoxetine

6

15,0

7

14,3

Sertraline

13

32,5

16

32,7

Escitalopram

3

7,5

11

22,4

Citalopram

2

5,0

2

4,1

Paroxetine

7

17,5

8

16,3

Duloxetine

3

7,5

2

4,1

Venlafaxine

3

7,5

2

4,1

Vortioxetine

3

7,5

1

2,0

Total

40

100,0

49

100,0

Table 3: Metabolic parameters that use in VAI formulation and VAI mean scores of Patients and Control group

 

MAJOR DEPRESSIVE DISORDER

ANXIETY DISORDERS

Control

p

HDL mg/dL

45.79±14.81

49.10±10.38

51.8±8.6

0.164

Thyrigliceride mg/dL

168.66±135.27

133.40±65.86

102.5±23.8

0.028*

VAI

8.18 ± 8.46

4.90±2.85

3.85±1.33

<0.001*

*p<0.05

Table 4: Linear Regression Model for Prediction of HamD Scores in Patients with MDD

Variable

B

%95 CI

p

VAI

0.315

0.011

0.581

0.042*

Age

0.350

0.015

0.427

0.036*

Sex

-0.192

-8.25

2.11

0.237

Education

-0.097

-0.990

0.52

0.534

CI: Confidence interval, B : Standardized coefficient for the constant*p<0.05

The HDRS total score mean value was determined as 25.25 + 7.95 for patients with MDD. The HARS total score mean value was determined as 21.14 + 5.75 for patients with ADs. The VAI score mean value was determined as 8.18 ± 8.46 for patients with MDD and 4.90 ± 2.85 for patients with ADs. There were significant differences between groups in terms of Thyrigliceride levels and VAI. When we examined the ADs and MDD groups in post hoc analysis, we found that there was no difference between patients with ADs and the control group in terms of VAI (0.072). However VAI was significantly higher in patients with MDD than control group (p=0.008). There was no difference between ADs and MDD (0.068). Also Thyrigliceride level was higher both in patient groups with MDD (p=0.012) and ADs (p=0.010) than control. Table 3 shows the metabolic parameters that use the VAI formulation in both patient groups and control group.

There was a positive correlation between VAI and HDRS in patients with MDD (P = 0.034 r: 0.336), whereas there was no significant correlation between VAI and HARS in patients with ADs (P = 0.610 r: −0.075).

BMI classified as normal weight (BMI 19 - <25 kg/m2), overweight (BMI 25 - <30 kg/m2) and obese (BMI ≥30 kg/m2). 59 % (29/49) patients with ADs had a normal weight.

In the multiple linear regression analysis model for MDD and ADs, ANOVA results were p = 0.05 and p = 0.88, respectively. Age and VAI were found to be statistically significant factors influencing the HDRS. Multiple regression analysis revealed significant associations between HDRS and VAI after adjusting for age, gender, and educational levels (p = 0.042) (Table 4).

Discussion

In this study, the relationships between depression/anxiety symptom levels and VAI were examined for patients with MDD and ADs who are non-responders to first-line SSRI/SNRI. First we found that VAI was higher in patients with MDD not in Patients with ADs than controls. While there was no significant correlation between VAI and anxiety scores in patients with ADs, there was a positive significant correlation between VAI and depression scores in patients with MDD.

In the regression analysis, it was determined that VAI predicted the severity of depression according to the HDRS scale. In similar studies; Rose et al. found a strong association between depressive symptoms and VAT in middle-aged women23. Lee et al. found that depressive mood is associated with VAT in overweight premenopausal women. However, in both studies, the participants did not suffer from MDDs. Coryell et al. found that MDD was associated with increased fat mass among overweight/obese adolescences (24), and Alshehri et al. found that measures of adiposity were associated with a depressive mood in a graded fashion14. Our study supports those findings in patients with MDD who are non-responders to SSRI/SNRI. Similarly, Papakostas et al. found that a greater body weight without obesity predicted non-response to SSRI17.

In our study, the significance of visceral adiposity in mood disorders such as major depression is, again, noticeable. How might visceral adiposity contribute to the severity of depression? VAT and mood disorders are interconnected with the inflammation of the biological roots of depression25. As there are too many studies that support the subclinical inflammation in mood disorders, many studies found higher levels of obesity, abdominal obesity, metabolic syndrome, and BMI which are related to increased visceral adiposity in patients with mood disorders9,14,26. Also higher Thyrigliceride level in patients with MDD may be contributed metabolic breakdown. These results are not surprising, considering VAT secretes cytokines and adipokines and may be creating a pre-inflammatory condition in mood disorders. Another issue is that depression may lead to an increase in VAT. Depression often causes an increase in cortisol, and this chronic stimulation can lead to an increase in VAT.

There were no significant differences between patients with ADs and control group in terms of VAI scores, and there was no association between VAI and anxiety scores in patients with ADs. A meta-analysis by Amiri showed a higher frequency of anxiety in obese/overweight groups than normal weight in terms of some subgroups (sex, obesity and anxiety assessment, adjusted/unadjusted, anxiety duration and age)15. Anxiety was found to be associated with excess adiposity when controlling for other emotional factors as depression and hostility/anger27. Diagnoses of social phobia, panic disorder, or dysthymia were found to have led to significantly increased weight circumferences and/or BMI in boys28. Hillman et al. found that symptoms of anxiety were associated with percentage body fat among adolescent females using another objective measure of adiposity with body fat percentage using dual-energy X-ray absorptiometry. In our study, no significant relationship was observed in the measurement of patients’ adiposity diagnosed with ADs, unhealthy adolescents/adults, or non-obese groups. However, in our study, most of the patients (29/49) with ADs had a normal weight (BMI: 19−25). Low numbers of obese or overweight patients may have affected the results.

The most important limitations of this current study are the small number of patients and the lack of control groups with a similar number of subjects. Since the VAI values of the patients were not known before drug treatment, the change after treatment with antipsychotics is not known. Another limitation of this study is the lack of data on the illness duration and all the treatment history of patients enrolled in our study to clarify the effects on the severity of symptoms. Anxiety is frequently comorbid with depression; therefore, we could not assert that patients with MDD had no anxiety symptoms.

Conclusion

In conclusion, it was observed that there was a positive relationship between VAI and depression severity in patients with MDD who did not respond to SSRI and/or SNRI treatment, but there was no similar relationship between anxiety symptom severity and VAI in patients with ADs. It may be thought that VAT, which may have an important role in the physiopathology and severity of depression, may not play a similar role in the physiopathology and severity of anxiety in patients with ADs. Large-scale prospective studies are needed to clarify the relationship between depression/anxiety severity and VAT and their relationship with the response to treatment.

Conflict of Interest Statement

There is no conflict of interest

Acknowledgements

Authors would like to thank Enago for English language review

All of the authors declare that there are no conflicts of interest in connection with this paper. Authors would like to thank Enago for English language review.

References

  1. Bandelow B. Comparison of the DSM–5 and ICD–10: panic and other anxiety disorders. CNS spectrums. 2017;22(5):404-6.
  2. Uher R, Payne JL, Pavlova B, Perlis RH. Major depressive disorder in DSM‐5: Implications for clinical practice and research of changes from DSM‐IV. Depression and anxiety. 2014;31(6):459-71.
  3. Amato MC, Giordano C, Galia M, Criscimanna A, Vitabile S, Midiri M, et al. Visceral Adiposity Index: a reliable indicator of visceral fat function associated with cardiometabolic risk. Diabetes care. 2010;33(4):920-2.
  4. Britton KA, Massaro JM, Murabito JM, Kreger BE, Hoffmann U, Fox CS. Body fat distribution, incident cardiovascular disease, cancer, and all-cause mortality. Journal of the American College of Cardiology. 2013;62(10):921-5.
  5. Biswas E, Choudhury A, Amin M, Khalequzzaman M, Chowdhury S, Kabir F, et al. Visceral Adiposity Index Score is the Better Predictor of Clinical and Coronary Angiographic Severity Assessment than Other Adiposity Indices in Patients with Acute Coronary Syndrome. Mymensingh medical journal: MMJ. 2019;28(2):382-8.
  6. Wang J, Liu EY, Freudenreich O, Goff D, Henderson DC, Fan X. Phenotypic characteristics in metabolically obese but normal weight non-diabetic patients with schizophrenia. Schizophrenia research. 2010;124(1-3):49-53.
  7. Fain JN. Release of inflammatory mediators by human adipose tissue is enhanced in obesity and primarily by the nonfat cells: a review. Mediators of inflammation. 2010;2010.
  8. Kahl KG, Deuschle M, Stubbs B, Schweiger U. Visceral adipose tissue in patients with severe mental illness. Hormone molecular biology and clinical investigation. 2018;33(1).
  9. Coín-Aragüez L, Pavón FJ, Contreras A, Gentile A-M, Lhamyani S, De Diego-Otero Y, et al. Inflammatory gene expression in adipose tissue according to diagnosis of anxiety and mood disorders in obese and non-obese subjects. Scientific reports. 2018;8(1):1-10.
  10. Konarzewska B, Stefańska E, Wendołowicz A, Cwalina U, Golonko A, Małus A, et al. Visceral obesity in normal-weight patients suffering from chronic schizophrenia. BMC psychiatry. 2014;14(1):35.
  11. Cho SJ, Lee HJ, Rhee SJ, Kim EY, Kim K-N, Yoon DH, et al. The relationship between visceral adiposity and depressive symptoms in the general Korean population. Journal of affective disorders. 2019;244:54-9.
  12. Murabito JM, Massaro JM, Clifford B, Hoffmann U, Fox CS. Depressive symptoms are associated with visceral adiposity in a community‐based sample of middle‐aged women and men. Obesity. 2013;21(8):1713-9.
  13. Hillman JB, Dorn LD, Huang B. Association of anxiety and depressive symptoms and adiposity among adolescent females, using dual energy X-ray absorptiometry. Clinical pediatrics. 2010;49(7):671-7.
  14. Alshehri T, Boone S, de Mutsert R, Penninx B, Rosendaal F, le Cessie S, et al. The association between overall and abdominal adiposity and depressive mood: A cross-sectional analysis in 6459 participants. Psychoneuroendocrinology. 2019;110:104429.
  15. Amiri S, Behnezhad S. Obesity and anxiety symptoms: A systematic review and meta-analysis. neuropsychiatrie. 2019;33(2):72-89.
  16. Jantaratnotai N, Mosikanon K, Lee Y, McIntyre RS. The interface of depression and obesity. Obesity research & clinical practice. 2017;11(1):1-10.
  17. Papakostas GI, Petersen T, Iosifescu DV, Burns AM, Nierenberg AA, Alpert JE, et al. Obesity among outpatients with major depressive disorder. International Journal of Neuropsychopharmacology. 2005;8(1):59-63.
  18. Patterson B, Van Ameringen M. Augmentation Strategies for Treatment-Resistant Anxiety Disorders: A Systematic Review and Meta-Analysis. Focus. 2017;15(2):219-26.
  19. Hamilton M. A rating scale for depression. Journal of neurology, neurosurgery, and psychiatry. 1960;23(1):56.
  20. Akdemir A, Örsel S, Dağ İ, Türkçapar H, İşcan N, Özbay H. Hamilton Depresyon Derecelendirme Ölçeği (HDDÖ)’nin geçerliği, güvenirliği ve klinikte kullanımı. Psikiyatri Psikoloji Psikofarmakoloji Dergisi. 1996;4(4):251-9.
  21. Hamilton M. The assessment of anxiety states by rating. British journal of medical psychology. 1959;32(1):50-5.
  22. Yazıcı M, Demir B, Tanrıverdi N, Karaağaoğlu E, Yolaç P. Hamilton Anksiyete Değerlendirme Ölçeği, değerlendiriciler arası güvenirlik ve geçerlik çalışması. Türk Psikiyatri Dergisi. 1998;9(2):114-7.
  23. Everson-Rose SA, Lewis TT, Karavolos K, Dugan SA, Wesley D, Powell LH. Depressive symptoms and increased visceral fat in middle-aged women. Psychosomatic medicine. 2009;71(4):410.
  24. Coryell WH, Butcher BD, Burns TL, Dindo LN, Schlechte JA, Calarge CA. Fat distribution and major depressive disorder in late adolescence. The Journal of clinical psychiatry. 2016;77(1):84.
  25. Milaneschi Y, Simmons WK, van Rossum EF, Penninx BW. Depression and obesity: evidence of shared biological mechanisms. Molecular psychiatry. 2019;24(1):18-33.
  26. Sahin SK, Elboga G, Kilic OHT, Sahin AZ, Unal A, Altindag A. Metabolic syndrome in patients with schizoaffective disorder and relationship with the antipsychotics. Acta medica mediterranea. 2018;34(1):133-7.
  27. Hawkins MA, Stewart JC. Do negative emotional factors have independent associations with excess adiposity? Journal of psychosomatic research. 2012;73(4):243-50.
  28. Aparicio E, Canals J, Voltas N, Hernández-Martínez C, Arija V. Emotional psychopathology and increased adiposity: Follow-up study in adolescents. Journal of adolescence. 2013;36(2):319-30.