The Prevalence of Anxiety and Depression in Breast Cancer Patients and their Correlation with Socio-Demographic Factors

  1. Apoorva Dadheech ,
  2. Suman Kumawat ,
  3. Deepesh Sharma ,
  4. Ravinder Singh Gothwal ,
  5. Rohitashwa Dana ,
  6. Chetna Meena ,
  7. Naresh Kumar Saini

Vol 8 No 4 (2023)

DOI 10.31557/apjcc.2023.8.4.675-679

Abstract

Introduction: Being diagnosed with breast cancer or receiving surgery, radiation or chemotherapy as a treatment modality in itself is seen as a traumatic experience for many women. This emotional distress is in turn associated with reduced quality of life and can pose a negative influence on compliance with treatment. Ultimately leading to an elevated risk of mortality which is also seen as the sixth vital sign in cancer care.
Aim & Objectives: The purpose of our study is to estimate the prevalence of depression and anxiety in breast cancer patients and their correlation with socio-demographic factors.
Materials and Methods: A cohort of 140 breast cancer patients registered in the Department of Radiation Oncology, SMS medical College, Jaipur from January 2022 to December 2022 were recruited and interviewed with a structured questionnaire including socio-clinical and demographic factors and PHQ-2 and GAD-2 scales.
Results: Prevalence of depression among patients were 37.9% (53/140) and almost one third (33.6%, 47/140) of cases had anxiety. Around two thirds (69.3%, 97/140) cases had stage III breast cancer, followed by stage II in 23 (16.4%) cases and 20 (14.3%) cases had IV stage breast cancer. The place of residence, educational status, employment status, accompanying person and marital status emerged as significant predictors of depression risk, while age group, marital status and financial status were found to have statistically significant association with elevated anxiety symptoms.
Conclusion: This study shows that prevalence of anxiety and depression in breast cancer patients is high and patients from rural areas, single, low monthly income, younger age group and low education level were more prone. Therefore, special care and support and often referral to psychiatry department may be required in such group of patients.

Introduction

All over the world, Breast cancer is a major public health problem among women. According to GLOBOCON 2020, it is the most diagnosed cancer globally accounting for every 1 in 10 (11.7%) newly diagnosed cancer cases, for the first-time surpassing lung cancer (11.4%). Breast cancer is the most common cancer among women in India, which accounts for accounting for 26.3% of all cancers in women [1]. In 2021, 627 cases of Carcinoma breast cancer presented to the outpatient department of Radiation Oncology, Sawai Man Singh Medical College and Hospital. Being diagnosed with breast cancer or receiving treatment for it which mainly comprises of mastectomy (surgery), radiotherapy or chemotherapy or in combination, is itself a traumatic experience to women and therefore, many breast cancer patients have intense fear toward their disease and the ongoing treatment process, and many of them even have psychiatric morbidities [2]. This emotional distress in patients is associated with a reduction in overall quality of life, and influences compliance levels with medical treatment negatively, and hence results in an elevated risk of mortality, this is why emotional distress is also called as the sixth vital sign in cancer care [3]. Breast cancer and its treatment can lead to many health issues such as lymphedema, pain, early menopause, and sexual problems [4], along with psychosocial ill effects like anxiety, depression, and self-image concerns [5-7]. Compared to general population, there have been increasing rates of depression in cancer patients. It is 25% rate overall and differs for different cancers- Oropharyngeal 22-57%;Pancreatic 33-50%; Breast 1.5-46%; Lung 11-44% [8].Treatment options include psychological interventions and yoga or classic pharmacotherapy, such as antidepressants, in cases of true depression [9].

Aims and Objectives

Purpose of our study is to estimate the prevalence of depression and anxiety in breast cancer patients in their first year of diagnosis and treatment and their correlation with socio-demographic factors such as age, sex, residence, education level, accompanying person at visit, financial and marital status at a tertiary care hospital. objectives were to assess the socio-demographic distribution of breast cancer patients visiting a tertiary care hospital and to assess the prevalence of anxiety and depression in the breast cancer patients and also to identify the correlation in between the socio-demographic factors and the presence of anxiety and depression among these patients.

Materials and Methods

A cohort of 140 randomly selected breast cancer patients who came for visit in the outpatient department registered in Department of Radiation, SMS medical College, Jaipur from January 2022 to December 2022 were recruited. All patients, except one, were women and were in their first year of treatment and diagnosis. The inclusion criteria were-18 or more years of age, histologically documented diagnosis of breast cancer, no history of prior mental disorder and dementia, no abuse of alcohol or drugs, adequate knowledge of the Hindi/English language and satisfactory level of communication, and consent to participate in the study. There were no restrictions with regard to histology of breast cancer, disease stage and demographic characteristics. The basic sociodemographic (age, place of residence, marital status, number of children, educational level), and clinical (surgical therapy, adjuvant therapy, stage of breast cancer) data were collected. The Patient Health Questionnaire-2 (PHQ-2) and the Generalized Anxiety Disorder-2 (GAD-2) questionnaire were used. In both questionnaires, each question requires respondents to rate on a four-point scale ranging from “0 = not at all” to “3 = nearly every day”. PHQ-2 and GAD-2 total scores are calculated by adding the two questions score, resulting in a range from 0 to 6 for each questionnaire, with higher score indicative of higher mental health disorder. According to receiver-operating characteristic curve analysis, the optimal cut point is ≥ 3 on both the PHQ-2 and GAD-2 scales [10-12].

Statistical Analysis-Data were analyzed using SPSS version 16. For univariate analysis, descriptive analysis was used while for bivariate analysis, Chi-square test and Correlation test were used. Univariate binary logistic regression was done to calculate the odd’s ratio.

Results

Around two thirds (69.3%,97/140) cases had stage III breast cancer, followed by stage II in 23 (16.4%) cases and 20 (14.3%) cases had IV stage breast cancer. Majority of the patients were from rural background (75.7%), most commonly presenting in the age group of 40-50 years (57.1%), and with low education and financial levels (Table1) shows the various characteristics of the patients. Prevalence of depression among patients were 37.9% (53/140) and almost one third (33.6%, 47/140) of cases had anxiety.

Table 1. Distribution of Different Patient’s Characteristics.

Variables Frequency   Percentage
Age Group (Years) <40 32 22.9
  40-49 42 30
  50-59 38 27.1
  60-69 21 15
  ≥70 7 5
Residence Rural 106 75.7
  Urban 34 24.3
Marital status Married 118 84.3
  Single 9 6.4
  Widow 13 9.3
No. of children 0 4 2.9
  02-Jan 92 65.7
  ≥3 44 31.4
Educational status Illiterate 84 60
  Primary 49 35
  Secondary 7 5
Employment status Dependent 118 84.3
  Employed 22 15.7
Per month income <10000 41 29.3
  10000-20000 81 57.9
  >20000 18 12.9
Accompanying person Family 100 71.4
  Neighbour 17 12.1
  Own 23 16.4
Depression Absent 87 62.1
  Present 53 37.9
Anxiety Absent 93 66.4
  Present 47 33.6
Staging of Breast Cancer II 23 16.4
  III 97 69.3
  IV 20 14.3
Total   140 100

Association of presence of depression with residence, educational status and employment status was found to be statistically insignificant (p value>0.05). While age group, marital status, per month income and accompanying person was significantly associated with presence of depression. Lower age group was protective factor for presence of depression. Lesser per month income was a risk factor for presence of depression. Patients having Rs.10000 monthly income were at 10 times higher risk of developing depression compared to patients with Rs.20000 monthly income. Patients coming to hospital with family/ neighbour were at lower risk of having depression compared to patients coming own their own. Table 2 shows the association of depression with various variables.

Table 2. Association of ِDepression with Different Variables.

Variables   Depression   p value OR
    Absent (n=87) Present (n=53)    
Age Group (Years) <40 29 (33.3) 3 (5.7) <0.001 0.017 (0.02-0.195)
  40-49 31 (35.6) 11 (20.8)   0.059 (0.006-0.548)
  50-59 16 (18.4) 22 (41.5)   0.229 (0.025-2.095)
  60-69 10 (11.5) 11 (20.8)   0.183 (0.019-1.799)
  ≥70 1 (1.1) 6 (11.3)   1
Residence Rural 63 (72.4) 43 (81.1) 0.335 1.638 (0.712-3.769)
  Urban 24 (27.6) 10 (18.9)   1
Marital status Married 81 (93.1) 37 (69.8) <0.001 0.083 (0.018-0.394)
  Single 4 (4.6) 5 (9.4)   0.227 (0.031-1.679)
  Widow 2 (2.3) 11 (20.8)   1
Educational status Illiterate 49 (56.3) 35 (66) 0.304 4.286 (0.494-37.199)
  Primary 32 (36.8) 17 (32.1)   3.187 (0.354-28.687)
  Secondary 6 (6.9) 1 (1.9)   1
Employment status Dependent 75 (86.2) 43 (81.1) 0.575 1.453 (0.580-3.644)
  Employed 12 (13.8) 10 (18.9)   1
Per month income <10000 8 (9.2) 33 (62.3) <0.001 10.725 (2.957-38.905)
  10000-20000 66 (75.9) 15 (28.3)   0.591 (0.183-1.911)
  >20000 13 (14.9) 5 (9.4)   1
Accompanying person Family 72 (82.8) 28 (52.8) <0.001 0.170 (0.063-0.458)
  Neighbour 8 (9.2) 9 (17)   0.492 (0.134-1.801)
  Own 7 (8) 16 (30.2)   1

Association of presence of anxiety with residence, educational status and employment status was found to be statistically insignificant (p value>0.05) While age group, marital status per month income and accompanying person was significantly associated with presence of anxiety. Lower age group was protective factor for presence of anxiety. Lesser per monthly income was a risk factor for presence of anxiety. Patients having Rs. 10000 monthly income were at five times higher risk of developing anxiety compared to patients with Rs. 20000 monthly income.

Patients coming to hospital as accompanying person at lower risk of having anxiety compared to patients coming own their own. (Table 3) depicts the correlation of anxiety with various factors.

Table 3. Association of Anxiety with Different Variables.

Variables   Anxiety   p value OR
    Absent (n=93) Present (n=47)    
Age Group (Years) <40 29 (31.2) 3 (6.4) <0.001 0.078 (0.011-0.525)
  40-49 33 (35.5) 9 (19.1)   0.205 (0.039-1.085)
  50-59 18 (19.4) 20 (42.6)   0.833 (0.164-4.239)
  60-69 10 (10.8) 11 (23.4)   0.825 (0.147-4.628)
  ≥70 3 (3.2) 4 (8.5)   1
Residence Rural 69 (74.2) 37 (78.7) 0.703 1.287 (0.556-2.978)
  Urban 24 (25.8) 10 (21.3)   1
Marital status Married 85 (91.4) 33 (70.2) 0.004 0.173 (0.050-0.599)
  Single 4 (4.3) 5 (10.6)   0.556 (0.095-3.246)
  Widow 4 (4.3) 9 (19.1)   1
Educational status Illiterate 54 (58.1) 30 (63.8) 0.507 3.333 (0.383-29.006)
  Primary 33 (35.5) 16 (34)   2.909 (0.322-26.244)
  Secondary 6 (6.5) 1 (2.1)   1
Employment status Dependent 81 (87.1) 37 (78.7) 0.298 1.824 (0.723-4.600)
  Employed 12 (12.9) 10 (21.3)   1
Per month income <10000 14 (15.1) 27 (57.4) <0.001 5.014 (1.485-16.929)
  10000-20000 66 (71) 15 (31.9)   0.591 (0.183-1.911)
  >20000 13 (14) 5 (10.6)   1
Accompanying person Family 74 (79.6) 26 (55.3) 0.009 0.270 (0.106-0.690)
  Neighbour 9 (9.7) 8 (17)   0.684 (0.194-2.410)
  Own 10 (10.8) 13 (27.7)   1

Discussion

The purpose of this study was to assess the prevalence and associated factors of depression and anxiety in breast cancer patients, and to identify independent predictors of mental health disorders risk. According to our results, in 37.9% of the patients, depressive symptoms are present and the place of residence, educational status, employment status, accompanying person and marital status were found as significant predictors of depression risk. In addition of them 33.6% are experiencing anxiety symptoms and again, the place of residence, educational status, employment status and age emerged as significant predictors of elevated anxiety symptoms, with statistically significant association with age group, marital status and financial status.

In a study conducted by Hassan et al. it was found that the prevalence of anxiety and depression was 31.7% and 22.0% respectively [13]. Study by Hassan et al. [13] found age group, monthly income were associated with anxiety; whereas financial support and being single were the associated with depression. In our study, majority of patients had age group 41-60 years (57%) followed by age group 20-40 years (22.9%) women shows the highest prevalence of breast cancer. This finding is supported by the study conducted by Hassan et al. [13] which shows that the commonest age of breast cancer is between 40 to 49 years with mean age of 50 years. Another study conducted by Vahdaninia et al. [14] found that 38.4% of the patients experienced severe anxiety and 22.2% had severe depression. A study of breast cancer survivors from Germany with an average of 47 months follow-up demonstrated that 38% of the patients had moderate to high anxiety and 22% had moderate to high depression as measured with the HADS [15], which supports the findings in our study. They also found lower education level to be a predictor of psychological comorbidity in patients with breast cancer. This can be explained by the fact that patients with higher education levels have a greater opportunity to be aware about their disease and its related aspects. In our study also, majority of women were Illiterate or low education level and were found to be with the highest prevalence of breast cancer. For the impact of psychiatry morbidity due to education level, prevalence of anxiety and depression were more in women with Illiterate or low education level as compared with high education level (secondary or college/university).

In conclusion, there is a high prevalence of anxiety and depression among breast cancer patients. Being rural resident, older age group, single/widowed, having no accompanying person at visits, lower monthly income and being illiterate can be predicting factors associated with depression and anxiety in breast cancer patients. Early detection and proper referral can contribute in addressing those conditions and increase quality of life and survival in breast cancer patients as our study is consisting of majorly rural population which lacks proper communication of mental health issues faced by women.

References


  1. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries Sung H, Ferlay J, Siegel RL , Laversanne M, Soerjomataram I, Jemal A, Bray F. CA: a cancer journal for clinicians.2021;71(3). CrossRef
  2. Prevalence and psychosocial factors of anxiety and depression in breast cancer patients Lueboonthavatchai P. Journal of the Medical Association of Thailand = Chotmaihet Thangphaet.2007;90(10).
  3. Anxiety and depression after cancer diagnosis: prevalence rates by cancer type, gender, and age Linden W, Vodermaier A, Mackenzie R, Greig D. Journal of Affective Disorders.2012;141(2-3). CrossRef
  4. Psychosocial issues confronting young women with breast cancer Baucom DH , Porter LS , Kirby JS , Gremore TM , Keefe FJ . Breast Disease.2005;23. CrossRef
  5. Surviving and thriving? Bloom JR . Psycho-Oncology.2002;11(2). CrossRef
  6. Prevalence of depression, anxiety, and adjustment disorder in oncological, haematological, and palliative-care settings: a meta-analysis of 94 interview-based studies Mitchell AJ , Chan M, Bhatti H, Halton M, Grassi L, Johansen C, Meader N. The Lancet. Oncology.2011;12(2). CrossRef
  7. The prevalence and pharmacotherapy of depression in cancer patients Ng CG , Boks MPM , Zainal NZ , Wit NJ . Journal of Affective Disorders.2011;131(1-3). CrossRef
  8. Measuring somatic symptoms with the CES-D to assess depression in cancer patients after treatment: comparison among patients with oral/oropharyngeal, gynecological, colorectal, and breast cancer Wilgen CP , Dijkstra PU , Stewart RE , Ranchor AV , Roodenburg JLN . Psychosomatics.2006;47(6). CrossRef
  9. Improving quality of life after breast cancer: dealing with symptoms Pinto AC , Azambuja E. Maturitas.2011;70(4). CrossRef
  10. The Patient Health Questionnaire Somatic, Anxiety, and Depressive Symptom Scales: a systematic review Kroenke K, Spitzer RL , Williams JBW , Löwe B. General Hospital Psychiatry.2010;32(4). CrossRef
  11. Anxiety disorders in primary care: prevalence, impairment, comorbidity, and detection Kroenke K, Spitzer RL , Williams JBW , Monahan PO , Löwe B. Annals of Internal Medicine.2007;146(5). CrossRef
  12. A 4-item measure of depression and anxiety: validation and standardization of the Patient Health Questionnaire-4 (PHQ-4) in the general population Löwe B, Wahl I, Rose M, Spitzer C, Glaesmer H, Wingenfeld K, Schneider A, Brähler E. Journal of Affective Disorders.2010;122(1-2). CrossRef
  13. Anxiety and Depression among Breast Cancer Patients in an Urban Setting in Malaysia Hassan MR , Shah SA , Ghazi HF , Mohd Mujar NM , Samsuri MF , Baharom N. Asian Pacific journal of cancer prevention: APJCP.2015;16(9). CrossRef
  14. What do predict anxiety and depression in breast cancer patients? A follow-up study Vahdaninia Mariam, Omidvari Sepideh, Montazeri Ali. Social Psychiatry and Psychiatric Epidemiology.2010;45(3). CrossRef
  15. Psychological comorbidity and health-related quality of life and its association with awareness, utilization, and need for psychosocial support in a cancer register-based sample of long-term breast cancer survivors Mehnert A, Koch U. Journal of Psychosomatic Research.2008;64(4). CrossRef

Copyright

© Asian Pacific Journal of Cancer Care , 2023

Author Details

Apoorva Dadheech
SMS Medical College and Attached Hospital, Jaipur, India.

Suman Kumawat
SMS Medical College and Attached Hospital, Jaipur, India.

Deepesh Sharma
SMS Medical College and Attached Hospital, Jaipur, India.

Ravinder Singh Gothwal
SMS Medical College and Attached Hospital, Jaipur, India.
drravindragothwal@yahoo.com

Rohitashwa Dana
SMS Medical College and Attached Hospital, Jaipur, India.

Chetna Meena
SMS Medical College and Attached Hospital, Jaipur, India.

Naresh Kumar Saini
SMS Medical College and Attached Hospital, Jaipur, India.

How to Cite

Dadheech, A., Kumawat, S., Sharma, D., Gothwal, R., Dana, R., Meena, C., & Saini, N. (2023). The Prevalence of Anxiety and Depression in Breast Cancer Patients and their Correlation with Socio-Demographic Factors. Asian Pacific Journal of Cancer Care, 8(4), 675-679. https://doi.org/10.31557/apjcc.2023.8.4.675-679
  • Abstract viewed - 563 times
  • PDF (FULL TEXT) downloaded - 315 times
  • XML downloaded - 0 times