Prevalence and Determinants of Depression and Generalized Anxiety Disorder among Female Patients Diagnosed with Breast Cancer Attending Two Referral Health Care Centres in Kano State, Nigeria

Abstract

Background: Breast cancer is a major public health concern worldwide, with significant psychological implications. Depression and generalized anxiety disorder (GAD) are common comorbidities among cancer patients, potentially affecting treatment adherence, prognosis, and quality of life. Despite the increasing burden of breast cancer in Nigeria, limited research exists on the prevalence and determinants of these mental health disorders, particularly in Kano State, therefore, understanding the prevalence and determinants of these psychiatric disorders in this population is crucial for integrating mental health care into oncology services. Aim: This study aimed to determine the prevalence and determinants of depression and generalized anxiety disorder among female breast cancer patients attending two referral healthcare centers in Kano State, Nigeria. Materials and Methods: This cross-sectional study was conducted among 240 female breast cancer patients attending SOPD clinics at Aminu Kano Teaching Hospital and Murtala Muhammad Specialist Hospital, Kano. Participants were assessed using the Mini International Neuropsychiatric Interview (MINI Version 7.0) for depression and GAD. Socio-demographic (e.g., age, marital status, education) and clinical data (e.g., cancer stage, treatment type) were collected. Descriptive statistics were used to determine prevalence rates, while chi-square and Fisher’s exact test were used to analyze associations between depression and GAD. Factors that were significant in the bivariate analysis were subjected to binary logistic regression to determine independent determinants of depression and GAD. Statistical significance was set at p < 0.05. Results: The prevalence of depression among the participants was 63.7% (95% CI: 57.4 - 69.7%), and GAD was 23.1% (95% CI: 16.4 - 27%). Age at diagnosis (≥45 years) was the only independent determinant of depression (AOR: 1.994, 95% CI: 1.076 - 3.679, p = 0.028). Conclusion: This study revealed a high prevalence of depression and GAD among female patients with breast cancer with age at diagnosis as the only independent determinant of depression among the participants.

Share and Cite:

Ibrahim, A. , Salihu, A. , Garba, H. , Taura, A. , Chikaodiri, A. , Usman, U. , Ibrahim, G. , Danjumma, M. , Owolabi, D. , Suleiman, A. , Ibrahim, Y. , Yakub, H. , Garko, A. , Alhassan, G. and Sani, M. (2025) Prevalence and Determinants of Depression and Generalized Anxiety Disorder among Female Patients Diagnosed with Breast Cancer Attending Two Referral Health Care Centres in Kano State, Nigeria. Open Journal of Psychiatry, 15, 246-255. doi: 10.4236/ojpsych.2025.154020.

1. Introduction

Breast cancer is the most common malignancy among women worldwide [1], with significant physical and psychological burdens [2]. In low- and middle-income countries, including Nigeria, the psychological impact of breast cancer is often overlooked despite its significant effect on treatment adherence, quality of life, and overall prognosis [3]. Depression and Generalized Anxiety Disorder (GAD) are highly prevalent in cancer patients due to disease-related stressors, including uncertainty about prognosis, treatment side effects, and financial difficulties [4]. Biologically, breast cancer triggers inflammation, for example elevated IL-6 and TNF-alpha and hypothalamic-pituitary-adrenal (HPA) axis dys-regulation, contributing to depression [5]. Psychologically, fear of body image concerns, treatment side effects and mortality heightens anxiety [6]. Socially, stigma and financial burden in Nigeria may exacerbate mental health issues [7]. Globally, the prevalence of depression among breast cancer patients ranges from 0% to 58% [8], while Nigerian studies reported much lower rates (11.4% and 15.5%) [2] [9]. The prevalence of anxiety disorders among breast cancer patients is higher in western studies (e.g., Germany [10], the United States of America [11]) than in Nigeria [12]. These variations may reflect differences in healthcare access, cultural stigma and screening tools [13]. Socio-demographic associations with depression and GAD vary: a Nigerian study found no links [14], while others reported marital status, educational and income associations [15] [16]. Furthermore, a study in Greece linked age, place of domicile, religion, educational level and marital status to depression [8]. In Nigeria, cultural and religious beliefs shape mental health experiences, particularly in Kano State, where help-seeking is limited [17]. Clinical factors including cancer stage, duration of breast cancer before diagnosis, treatment modality [18], and recurrence [19], are strongly associated with depression and GAD. Few studies have explored these in Kano, where cultural and religious influences may shape mental health experiences and help-seeking behaviors.

2. Methodology

This cross-sectional study was conducted among female breast cancer patients at the surgical outpatient department (SOPD) clinics of Aminu Kano Teaching Hospital (AKTH) and Murtala Muhammad Specialist Hospital (MMSH), Kano State, Nigeria, over six months (September 2023 - February 2024). A systematic sampling method recruited 240 participants, with proportional allocation based on patient volume at each hospital. The first participant was selected using a random number table, followed by every second patient until the sample size was reached. Ethical approval was obtained from AKTH’s Research Ethics Committee (AKTH/ MAC/SUB/12A/P-3/VI/3748). Informed consent was obtained from all the participants.

Inclusion criteria: Women aged ≥ 18 years with a histopathologically confirmed breast cancer diagnosis.

Exclusion criteria: Participants with severe mental illness impairing response capability, severe medical conditions preventing participation, or pre-existing psychiatric disorders before breast cancer diagnosis were excluded from the study.

2.1. Procedure

Participants completed the Mini International Neuropsychiatric Interview (MINI 7.0) to diagnose depression and GAD, administered by trained interviewers in approximately 15 minutes. A socio-demographic and clinical questionnaire collected data on age, marital status, employment, religion, income, cancer stage, treatment type (e.g., chemotherapy, mastectomy), duration of illness (time since diagnosis: ≤ 1 year vs. ≥ 1 year), recurrence, and support source (relatives vs. others, e.g., friends, NGOs). The MINI 7.0, aligned with DSM-5, has high reliability and validity [20], and prior use in Nigeria [21].

2.2. Statistical Analysis

Data were analyzed using SPSS version 21. Descriptive statistics (frequencies, means and standard deviations) summarized characteristics. Prevalence was reported as proportions with 95% confidence intervals (CI). Chi-square or Fisher’s exact tests assessed associations at p < 0.05. Age at diagnosis was categorized (<45 vs. ≥45 years, based on menopausal and depression risk [22]). Whilst less common, breast cancer which occurs at the age less than 45 yrs is considered early onset, majority of breast cancers occurs at the age above 45 – 50 yrs. Significant bivariate factors were analyzed via binary logistic regression to identify independent determinants.

3. Results

Using the MINI-7, depression prevalence was 63.7% (95% CI: 57.4 - 69.7%) and GAD prevalence was 21.3% (95% CI: 16.4 - 27.0%) among 240 participants. Figure 1 (pie chart) illustrates depression prevalence, and Figure 2 shows GAD prevalence. Socio-demographic factors: Age (p = 0.001) and religion (p = 0.004) were associated with depression (Table 1). No socio-demographic factors were significantly associated with GAD (all p > 0.05). Table 1 details associations, with Christianity linked to higher depression (90.9% vs. 61.1% for Islam). Clinical Factors: Age at diagnosis (<45 vs. ≥45 years) was the only clinical factor associated with depression (p = 0.014), with no clinical factors linked to GAD (Table 2). Table 2 summarizes clinical associations.

Regression Analysis: Binary logistic regression of significant bivariate factors (age, religion, age at diagnosis) identified age at diagnosis (≥45 years) as the sole independent determinant of depression (AOR: 1.069, CI: 1.076 - 3.679, p = 0.028) (Table 3). The wide CI for the 20 - 29 age group (AOR: 1.069, CI: 0.105 - 10.891) reflects the small sample size (n = 33), reducing estimate precision.

Figure 1. Pie Chart showing the prevalence of depression among the participants.

Figure 2. Pie chart showing the prevalence of generalized anxiety disorder among the participants.

3.1. Socio-Demographic Factors Associated with Depression and GAD among the Participants

The socio-demographic factors associated with depression were the age of the participants p = 0.001 and religion p = 0.004 interestingly, no socio-demographic factor achieved statistical significance with GAD (Table 1). The two socio-demographic variables that had statistical significance with depression were subjected to binary logistic regression.

3.2. Clinical Factors Associated with Depression and GAD among the Participants

Age at diagnosis of breast cancer was the sole factor associated with depression among the participants p = 0.014, while no clinical factors were associated with depression among the participants (Table 2).

Table 1. Association between socio-demographic factors with depression and GAD among the participants.

Variables

Depressed (Frequency (%))

Non-depressed (Frequency (%))

χ2

p value

GAD

No-GAD

χ2

p value

Age(years)

14.987

0.001**

7.315

0.198

<20

10 (41.7%)

14 (58.3%)

4 (16.7%)

20 (83.3%)

20 - 29

25 (75.8%)

8 (24.2%)

9 (27.3%)

24 (72.7%)

30 - 39

30 (50.8%)

29 (49.2%)

6 (10.2%)

53 (89.8%)

40 - 49

48 (67.6%)

23 (32.4%)

19 (26.8%)

52 (73.2%)

50 - 59

21 (75.0%)

7 (25.0%)

6 (21.4%)

22 (78.6%)

≥60

19 (76.0%)

6 (24.0%)

7 (28.0%)

18 (72.0%)

Marital status

2.590

0.61

2.654

0.103

Married

97 (62.6%)

58 (37.4%)

28 (18.1%)

127 (81.9%)

Unmarried

56 (65.9%)

29 (34.1%)

23 (27.1%)

62 (72.9%)

Family type

2.660

0.27

0.411

0.944

Monogamy

100 (63.7%)

57 (36.3%)

34 (21.7%)

122 (78.3%)

Polygamy

53 (64.9%)

30 (36.1%)

16 (20.3%)

64 (79.7%)

Number of children

0.167

0.68

0.145

0.704

0 - 4

98 (62.8%)

58 (37.2%)

32 (20.5%)

124 (79.5%)

≥5

55 (65.5%)

29 (34.5%)

19 (22.6%)

65 (77.4%)

Religion

3.970

0.004**

0.477

0.490

Islam

140 (61.1%)

89 (38.9%)

48 (20.9%)

182 (79.1%)

Christianity

10 (90.9%)

1 (9.1%)

3 (30.0%)

7 (70.0%)

Educational status

0.856

0.355

0.221

0.638

High (≥12 years)

91 (61.5%)

57 (38.5%)

30 (20.3%)

118 (79.7%)

Low (<12 years)

62 (67.4%)

30 (32.6%)

21 (22.8%)

71 (77.2%)

Tribe

0.260

0.610

0.645

0.422

Hausa-Fulani

130 (63.1%)

76 (36.9%)

42 (20.4%)

164 (79.6%)

Others

23 (67.6%)

11 (32.4%)

9 (26.5%)

25 (73.5%)

Continued

Employment status

0.377

0.539

0.123

0.726

Employed

101 (65.2%)

54 (34.8%)

34 (21.9%)

121 (78.1%)

Unemployed

52 (61.2%)

33 (38.3%)

17 (20.0%)

68 (60.0%)

Monthly-income (Naira)

0.017

0.895

1.833

0.176

≤30,000

112 (64.0%)

63 (36.0%)

41 (23.4%)

134 (76.6%)

>30,000

41 (63.1%)

24 (36.9%)

10 (15.4%)

55 (84.6%)

Support source

3.744

0.053

0.205

0.651

Relatives

127 (61.4%)

80 (38.6%)

43 (20.8%)

164 (79.2%)

Others

26 (78.8%)

7 (21.2%)

8 (24.2%)

25 (75.8%)

**Statistically significant.

3.3. Clinical Factors Associated with Depression and GAD among the Participants

Age at diagnosis was the only clinical factor associated with depression p value = 0.014, while none of the clinical factors showed statistical significance with GAD among the participants (Table 2).

Table 2. Association between clinical factors with depression and GAD among the participants.

Variables

Depressed (Frequency (%))

Non-depressed (Frequency (%))

χ2

p-value

GAD

(Frequency (%))

No-GAD (Frequency (%))

χ2

p-value

Age at diagnosis (years)

6.101

0.014**

3.543

0.060

≤44

98 (58.7%)

69 (41.3%)

30 (18.0%)

137 (82.0%)

≥45

55 (75.3%)

18 (24.7%)

21 (28.8%)

52 (71.2%)

Duration of illness

0.342

0.558

0.053

0.819

≤1year

54 (61.4%)

34 (38.6%)

18 (20.5%)

70 (79.5%)

≥1year

99 (65.1%)

53 (34.9%)

33 (21.7%)

119 (78.3%)

Cancer stage

7.617

0.055

3.661

0.300

Stage 1

10 (62.5%)

6 (37.5%)

2 (12.5%)

14 (87.5%)

Stage 2

29 (49.2%)

30 (50.8%)

10 (16.9%)

49 (83.1%)

Stage 3

59 (67.8%)

28 (32.2%)

24 (27.6%)

63 (72.4%)

Stage 4

55 (70.5%)

23 (29.5%)

15 (19.2%)

63 (80.8%)

Treatment modality

4.067

0.254

6.904

0.075

Combination

81 (60.4%)

53 (39.6%)

28 (209.9%)

106 (79.1%)

Chemotherapy

40 (62.5%)

24 (37.5%)

14 (21.9%)

50 (78.1%)

Mastectomy

21 (72.4%)

8 (27.6%)

3 (10.3%)

26 (89.7%)

Not yet on treatment

11 (84.6%)

2 (15.4%)

6 (46.2%)

7 (53.8%)

Illness recurrence

0.921

0.337

0.141

0.707

Yes

42 (59.2%)

29 (40.8%)

14 (19.7%)

57 (80.3%)

No

111 (65.7%)

58 (34.3%)

37 (21.9%)

132 (78.1%)

Continued

Presence of lingering side effect

0.000

0.992

0.907

0.341

Yes

81 (63.8%)

46 (36.2%)

30 (23.6%)

97 (76.4%)

No

72 (63.7%)

41 (36.3%)

21 (18.6%)

92 (81.4%)

**Statistically significant.

3.4. Regression of Factors Associated with Depression and GAD among the Participants

Factors that were significant at the bivariate analysis such age of the participants, religion and age at diagnosis were subjected to binary logistic regression, only age at diagnosis was an independent determinant of depression among the participants. Participants who were diagnosed with breast cancer above the age of 45 years were 2 times more likely to be depressed than those who were diagnosed 44 years and below (AOR: 1.994, CI: 1.076 - 3.679, p-value 0.028) (Table 3).

Table 3. Analysis of factors associated with depression and GAD among the participants at logistic regression.

Variables

B

AOR

Confidence interval

p value

Upper

Lower

Age at diagnosis of cancer

0.690

1.994

1.076

3.697

0.028**

Age of participants (years)

<20

−20.999

0.000

0.000

0.999

20 - 29

0.067

1.069

0.105

10.891

0.955

30 - 39

−2.057

0.128

0.014

1.206

0.072

40 - 49

−0.378

0.685

0.084

5.609

0.724

50 - 59

1.105

3.021

0.519

17.567

0.128

Religion (Islam)

−1.827

0.161

0.020

1.303

0.087

Reference categories: Age at diagnosis of cancer: 44 years and below, Age of participants: 60 years and above, Religion: Christianity, ** statistically significant.

4. Discussion

The 63.7% prevalence of depression in this study is high, exceeding prior Nigerian studies (11.4 - 15.5%) [2] [9], and a South African study (36.6%) [23]. GAD prevalence (21.3%) is significantly higher than the general Nigerian population rate of 1.8% [24], and aligns with Southwest Nigerian cancer study (18.5%) [25] [26]. These differences may be due to confounders like limited healthcare access, higher stigma in Kano, and use of MINI 7.0 which is more sensitive than self-report tools used elsewhere [20]. Socio-cultural factors, including stigma and low mental health awareness, amplify psychological distress, with breast cancer often perceived as a “death sentence”. Age was associated with depression, particularly among the participants aged ≥60 and 20 - 29 years. Older women may face spousal loss, reduced independence, and physical decline, while younger women experience career disruptions and body image issues, lowering self-esteem [27]-[29], Religion influenced depression, with Christians showing higher prevalence (90.9% vs. 61.1% for Muslims). This variation may reflect differences in religious coping styles. Certain Islamic beliefs emphasizing acceptance of life challenges might offer some psychological buffering. Age at diagnosis (≥45 years) was the sole independent determinant of depression (AOR: 1.994), consistent with Vahdaninia et al. (2015) [30]. Older women perceive cancer as terminal, compounded by menopausal hormonal changes (e.g., low estrogen) [31]. No clinical factors, including recurrence, were associated with GAD, possibly due to the cross-sectional design’s inability to capture temporal anxiety triggers.

5. Limitations

The cross-sectional design precludes causal inferences, as depression and GAD may precede or follow cancer diagnosis. The hospital-based sample may limit generalizability to community settings. The wide CI for the 20 - 29 age group’s GAD estimate (n = 33) indicates low precision due to small subgroup size.

6. Clinical Implications

Routine screening should be integrated into oncology clinics, prioritizing women diagnosed at ≥45 years. Counselling services, for older and younger patients, can address stigma and body image concerns. Training health care workers in oncology unit in empathetic communication can improve mental health support.

Conflicts of Interest

The authors declare no conflicts of interest regarding the publication of this paper.

References

[1] Bray, F., Ferlay, J., Soerjomataram, I., Siegel, R.L., Torre, L.A. and Jemal, A. (2018) Global Cancer Statistics 2018: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA: A Cancer Journal for Clinicians, 68, 394-424.
https://doi.org/10.3322/caac.21492
[2] Opadola, O., Alatishe, T., Suleiman, B. and Ojedokun, S. (2022) Prevalence of Major Depressive Disorder in Patients Diagnosed with Breast Prevalence of Major Depressive Disorder in Patients Diagnosed with Breast Cancer in Southwest Nigeria. International Research Journal of Oncology, 6, 18-25.
[3] Opia, F.N. and Matthew, K.A. (2025) Socioeconomic Disparities in Breast Cancer Care: Addressing Global Challenges in Oncology Outcomes. International Journal of Computer Applications Technology and Research, 14, 39-52.
[4] Yanez, B., Perry, L.M., Peipert, J.D., Kuharic, M., Taub, C., Garcia, S.F., et al. (2024) Exploring the Relationship among Financial Hardship, Anxiety, and Depression in Patients with Cancer: A Longitudinal Study. JCO Oncology Practice, 20, 1776-1783.
https://doi.org/10.1200/op.24.00025
[5] Young, K. and Singh, G. (2018) Biological Mechanisms of Cancer-Induced Depression. Frontiers in Psychiatry, 9, Article 299.
https://doi.org/10.3389/fpsyt.2018.00299
[6] Salmanian, K.S.K., Fatemeh, F.S.M., Marashian, S. and Lezcano, G. (2022) Prediction of Death Anxiety Based on Body Image Concerns Mediated by Disease Perception in Patients with Breast Cancer. Clinical Social Work and Health Intervention, 13, 61-66.
[7] Esan, O. and Esan, A. (2015) Epidemiology and Burden of Bipolar Disorder in Africa: A Systematic Review of Data from Africa. Social Psychiatry and Psychiatric Epidemiology, 51, 93-100.
https://doi.org/10.1007/s00127-015-1091-5
[8] Tsaras, K., Papathanasiou, I.V., Mitsi, D., Veneti, A., Kelesi, M., Zyga, S., et al. (2018) Assessment of Depression and Anxiety in Breast Cancer Patients: Prevalence and Associated Factors. Asian Pacific Journal of Cancer Prevention, 19, 1661-1669.
[9] Amoran, O., Lawoyin, T. and Lasebikan, V. (2007) Prevalence of Depression among Adults in Oyo State, Nigeria: A Comparative Study of Rural and Urban Communities. Australian Journal of Rural Health, 15, 211-215.
https://doi.org/10.1111/j.1440-1584.2006.00794.x
[10] Goerling, U., Hinz, A., Koch-Gromus, U., Hufeld, J.M., Esser, P. and Mehnert-Theuerkauf, A. (2023) Prevalence and Severity of Anxiety in Cancer Patients: Results from a Multi-Center Cohort Study in Germany. Journal of Cancer Research and Clinical Oncology, 149, 6371-6379.
https://doi.org/10.1007/s00432-023-04600-w
[11] Stark, D., Kiely, M., Smith, A., Velikova, G., House, A. and Selby, P. (2002) Anxiety Disorders in Cancer Patients: Their Nature, Associations, and Relation to Quality of Life. Journal of Clinical Oncology, 20, 3137-3148.
https://doi.org/10.1200/jco.2002.08.549
[12] Walker, Z.J., Jones, M.P. and Ravindran, A.V. (2017) Psychiatric Disorders among People with Cancer in Low-and Lower-Middle-Income Countries: Study Protocol for a Systematic Review and Meta-analysis. BMJ Open, 7, e017043.
https://doi.org/10.1136/bmjopen-2017-017043
[13] Akhigbe, A. and Akhigbe, K. (2016) Effects of Health Belief and Cancer Fatalism on the Practice of Breast Cancer Screening among Nigerian Women. In: Uchiyama, N. and do Nascimento, M.Z., Eds., MammographyRecent Advances, InTech Open, 4-85.
[14] Lasebikan, V. and Fakunle, S. (2020) Twelve-Month Prevalence of Psychiatric Morbidity in Cancer Patients in a Nigerian Oncology Centre.
[15] Popoola, A.O. and Adewuya, A.O. (2011) Prevalence and Correlates of Depressive Disorders in Outpatients with Breast Cancer in Lagos, Nigeria. Psycho-Oncology, 21, 675-679.
https://doi.org/10.1002/pon.1968
[16] Elumelu, T.N., Asuzu, C.C. and Akin-Odanye, E.O. (2014) Impact of Active Coping, Religion and Acceptance on Quality of Life of Patients with Breast Cancer in the Department of Radiotherapy, UCH, Ibadan. BMJ Supportive & Palliative Care, 5, 175-180.
https://doi.org/10.1136/bmjspcare-2012-000409
[17] Idi, M., Baba, M.U., Polytechnic, K.S., Adamu, S.A., Polytechnic, K.S., Yahaya, Y., et al. (2020) Statistical Study on Knowledge & Awareness of Breast Cancer Statistical Study on Knowledge & Awareness of Breast Cancer among Women within Reproductive Age, A Reference to Fagge L.G.A. of Kano State. International Journal of Advanced Academic Research, 6, 170-180.
[18] Mir, M.T., Kumari, R., Gupta, R.K., Sharma, R., Gul, N. and Langer, B. (2023) Psychiatric Comorbidities and Breast Cancer: A Study from Jammu Region of UT of J&K, India. Journal of Cancer Research and Therapeutics, 19, S545-S550.
https://doi.org/10.4103/jcrt.jcrt_1081_22
[19] Wang, X., Wang, N., Zhong, L., Wang, S., Zheng, Y., Yang, B., et al. (2020) Prognostic Value of Depression and Anxiety on Breast Cancer Recurrence and Mortality: A Systematic Review and Meta-Analysis of 282,203 Patients. Molecular Psychiatry, 25, 3186-3197.
https://doi.org/10.1038/s41380-020-00865-6
[20] Sheehan, D.V., Lecrubier, Y., Sheehan, K.H., et al. (1998) The Mini-International Neuropsychiatric Interview (M.I.N.I.): The Development and Validation of a Structured Diagnostic Psychiatric Interview for DSM-IV and ICD-10. The Journal of Clinical Psychiatry, 59, 22-23.
[21] Fakorede, O.O., Ogunwale, A. and Akinhanmi, A.O. (2019) Disability among Patients with Schizophrenia: A Hospital-Based Study. International Journal of Social Psychiatry, 66, 179-187.
https://doi.org/10.1177/0020764019894608
[22] Avis, N.E., Crawford, S. and Manuel, J. (2005) Quality of Life among Younger Women with Breast Cancer. Journal of Clinical Oncology, 23, 3322-3330.
https://doi.org/10.1200/jco.2005.05.130
[23] Author, C., Matieland, P., Africa, S., Add, E., Matieland, P. and Africa, S. (2022) Psychosocial Predictors of Distress and Depression among South African Breast Cancer Patients. South African Journal of Psychology, 52, 392-403.
[24] Al-hamzawi, A., Alonso, J., Andrade, L.H., Borges, G., Levinson, D., Mneimneh, Z., et al. (2017) Cross-Sectional Comparison of the Epidemiology of DSM-5 Generalized Anxiety Disorder Across the Globe. JAMA Psychiatry, 74, 465-475.
[25] Burgess, C., Cornelius, V., Love, S., Graham, J., Richards, M. and Ramirez, A. (2005) Depression and Anxiety in Women with Early Breast Cancer: Five Year Observational Cohort Study. BMJ, 330, 702.
https://doi.org/10.1136/bmj.38343.670868.d3
[26] Akarolo-Anthony, S.N., Ogundiran, T.O. and Adebamowo, C.A. (2010) Emerging Breast Cancer Epidemic: Evidence from Africa. Breast Cancer Research, 12, Article No. S8.
https://doi.org/10.1186/bcr2737
[27] Li, Y., Liu, H., Sun, Y., Li, J., Chen, Y., Zhang, X., et al. (2021) Characteristics and Subtypes of Depressive Symptoms in Chinese Female Breast Cancer Patients of Different Ages: A Cross-Sectional Study. AIMS Public Health, 8, 691-703.
https://doi.org/10.3934/publichealth.2021055
[28] Zhang, Q., Wu, G., Chen, J., Fang, K., Liu, Q., Zhang, P., et al. (2024) Factors Influencing Depressive Symptoms in Chinese Female Breast Cancer Patients: A Meta-Analysis. Frontiers in Psychology, 15, Article 1332523.
https://doi.org/10.3389/fpsyg.2024.1332523
[29] Salem, H. and Daher-Nashif, S. (2020) Psychosocial Aspects of Female Breast Cancer in the Middle East and North Africa. International Journal of Environmental Research and Public Health, 17, Article 6802.
https://doi.org/10.3390/ijerph17186802
[30] Vahdaninia, M., Omidvari, S. and Montazeri, A. (2009) What Do Predict Anxiety and Depression in Breast Cancer Patients? A Follow-Up Study. Social Psychiatry and Psychiatric Epidemiology, 45, 355-361.
https://doi.org/10.1007/s00127-009-0068-7
[31] Freeman, E.W., Sammel, M.D., Lin, H. and Nelson, D.B. (2006) Associations of Hormones and Menopausal Status with Depressed Mood in Women with No History of Depression. Archives of General Psychiatry, 63, 375-382.
https://doi.org/10.1001/archpsyc.63.4.375

Copyright © 2025 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.