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ORIGINAL RESEARCH article

Front. Psychiatry, 08 October 2025

Sec. Mood Disorders

Volume 16 - 2025 | https://doi.org/10.3389/fpsyt.2025.1667902

Impact of comorbid depression on quality of life and disease progression in chronic obstructive pulmonary disease: a correlational analysis

Yu ChenYu Chen1Qianqian GaoQianqian Gao2Hongqin JiaHongqin Jia1Kang QianKang Qian1Hongbin Zhu*Hongbin Zhu3*
  • 1The Fourth Affiliated Hospital of Anhui Medical University, Chaohu, China
  • 2Department of Respiratory and Critical Care Medicine, Fuyang People's Hospital, Fuyang, China
  • 3Department of Respiratory and Critical Care Medicine, The Fourth Affiliate Hospital of Anhui Medical University, Chaohu, China

Introduction: Depression is a prevalent comorbidity in patients with Chronic Obstructive Pulmonary Disease (COPD), particularly during acute exacerbations (AECOPD), significantly impacting prognosis and quality of life. This study aimed to investigate the risk factors and severity of depression in this population.

Objective: To identify risk factors and assess depression severity in patients experiencing Acute Exacerbation of Chronic Obstructive Pulmonary Disease (AECOPD).

Methods: AECOPD patients admitted to Chaohu Hospital Affiliated with Anhui Medical University, between October 2023 and February 2025 were included. Participants were divided into four groups using the Patient Health Questionnaire-9 (PHQ-9): mild depression group (n=86), moderate depression group (n=24), severe depression group (n=3), and a control group without depression (n=156). Data collection involved: the first two domains of the World Health Organization Quality of Life questionnaire (WHOQOL-BREF), The Social Impact Scale (SIS) for stigma assessment Clinical data, treatment history, and laboratory test results. A custom-designed questionnaire was utilized to record hospitalization details for intergroup comparisons.

Results: This study included 269 AECOPD patients, comprising 113 cases in the depression group and 156 controls. Comparative analysis revealed that female patients, those with longer smoking histories, theophyllines users, individuals with greater disease severity, stronger perceived stigma, and poorer quality of life demonstrated higher susceptibility to depression. In depression severity subgroups, 86 cases were classified as mild depression while 27 cases exhibited moderate-to-severe depression. The results demonstrated that gender, glucocorticoid use, daily cigarette consumption, and prolonged hospitalization were significantly associated with aggravated comorbid depression in COPD patients.

Conclusion: Depressive state in patients with AECOPD is clinically common and associated with factors including gender, smoking history, MMRC grade, disease severity, hospitalization duration, theophyllines use, as well as quality of life and stigma.

1 Introduction

Chronic obstructive pulmonary disease (COPD) is a prevalent yet preventable and treatable condition characterized by persistent respiratory symptoms and airflow limitation, primarily caused by prolonged exposure to noxious particles or gases like tobacco smoke (1). A major global health challenge, COPD ranks third leading cause of death and seventh highest health risk worldwide (2), with a 2022 age-standardized mortality rate of 10.44 per 100,000 (3).

Depression, a psychiatric disorder, features persistent depressed mood, anhedonia, and associated symptoms like psychomotor changes, fatigue, and impaired concentration (4). It also presents vegetative symptoms and exhibits high comorbidity with medical/psychiatric disorders, significant prevalence, and elevated recurrence/disability risks (5).

COPD frequently coexists with depression (6, 7), often underdiagnosed due to prioritization of respiratory symptoms (8, 9). GOLD emphasizes integrating depression screening. Prevalence is 10–42% in stable COPD and 10–86% during exacerbations (10), with up to 55% exhibiting psychiatric comorbidities (11). Major depressive disorder predominates. Depression interacts synergistically with modifiable risk factors like tobacco use, amplifying mortality (12).

Despite rising prevalence, depression’s risk factors in COPD remain poorly characterized (13). The specific role of inflammatory markers, oxidative stress parameters, and other objective laboratory data in conjunction pharmacological treatments and psychosocial measures during an exacerbation is poorly characterized. Our preliminary study found significant insomnia and depressive symptom comorbidity in AECOPD (14), prompting this investigation into determinants of depression. This study systematically examines associations between depressive states and laboratory biomarkers, medical history, and pharmacological interventions to inform targeted therapies.

2 Materials and methods

2.1 Study population

A total of 269 patients with Acute Exacerbation of Chronic Obstructive Pulmonary Disease (AECOPD), admitted to Chaohu Hospital Affiliated with Anhui Medical University between October 2023 and February 2025, were included in this study. Inclusion Criteria:(1) Diagnosis of COPD confirmed according to the 2023 Global Initiative for Chronic Obstructive Lung Disease (GOLD) diagnostic criteria. (2) Current hospitalization due to acute exacerbation, defined by rapid clinical deterioration requiring therapeutic modifications. Exclusion Criteria: (1) History of diagnosed psychiatric disorders, mental illness, or severe organ failure. (2) Use of antidepressants or sedatives within the past month. (3) Impaired consciousness or language dysfunction. (4) Visual or auditory impairments hindering questionnaire completion. The study protocol adhered to the principles of the Declaration of Helsinki and was approved by the Ethics Committee of Chaohu Hospital Affiliated with Anhui Medical University(Approval No.KYXM-202309-005). Written informed consent was obtained from all participants.

2.2 Data collection

(1) Baseline demographic data were collected through structured interviews, including age, sex, BMI, smoking history, widowhood status, educational level, comorbidities, mMRC dyspnea grade, and scores from depression, quality of life (QOL), and stigma assessments. (2) Clinical treatment data were extracted from medical records: annual hospitalization frequency, antibiotic types, theophyllines use, glucocorticoid administration methods, and current hospitalization duration. (3) Laboratory parameters from admission tests were recorded: complete blood count, hepatic/renal function, and coagulation panel.

2.3 Measurement tools

(1) Quality of Life (QOL): Evaluated using the first two domains of the World Health Organization Quality of Life Brief Version (WHOQOL-BREF), reflecting patients’ perceived health and life satisfaction. Higher total scores indicate better QOL. (2) Patient Health Questionnaire-9 (PHQ-9): Assessed depression severity over a 2-week period. Total scores range from 0–27 (each item scored 0–3):0–4: No/minimal depression, 5–9: Mild depression, 10–14: Moderate depression, 15–19: Moderately severe depression, ≥20: Severe depression; (3) Social Impact Scale (SIS): Measured perceived stigma using a 4-point Likert scale (1=“strongly disagree” to 4=“strongly agree”). Higher scores indicate greater stigmatization. (4) Modified Medical Research Council (mMRC) Dyspnea Scale: Graded COPD-related breathlessness:Grade 0: Dyspnea only during strenuous exercise, Grade 1: Shortness of breath when walking briskly or climbing slopes, Grade 2: Slower walking pace than peers due to breathlessness, Grade 3: Requires rest after walking 100 meters, Grade 4: Breathlessness at rest or during basic activities.

2.4 Statistical analysis

Data were analyzed using SPSS 27.0. This was an observational cross-sectional study without a priori sample size calculation. During the study period, 269 eligible patients with AECOPD were consecutively enrolled. A post-hoc power analysis indicated that, with quality of life (QOL) as the primary outcome, the observed between-group effect size was Cohen’s d≈1.36. Continuous variables with normal distribution were expressed as mean ± SD; non-normal data as median (IQR); categorical variables as n (%). Intergroup comparisons employed: Independent t-tests (normally distributed data with equal variances), Mann-Whitney U tests (non-normal/heteroscedastic data), Chi-square tests (categorical variables), Statistical significance was set at p < 0.05 (two-tailed).

3 Results

3.1 Clinical characteristics of AECOPD patients

The study included 269 patients, stratified into a depression group (n=113) and a control group (n=156) based on PHQ-9 scores. Significant differences (p < 0.05) were observed between groups in sex, smoking history, mMRC grades, stigma scores (SIS), and QOL scores. Specifically, the depression group exhibited a higher proportion of female patients, elevated smoking history, greater disease severity (higher mMRC grades), stronger perceived stigma, and poorer quality of life compared to controls. No statistically significant differences (p≥0.05) were found in age, BMI, marital status, comorbidities, educational attainment, hospitalization frequency, or length of hospital stay between groups (Table 1).

Table 1
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Table 1. The depression group demonstrated a significantly higher proportion of female patients compared to controls (p < 0.05).

3.2 Medication profiles of AECOPD patients

Significant differences in theophyllines use were observed between AECOPD patients with and without depression (p<0.05), with a higher prevalence of theophyllines utilization in the depression group. However, no statistically significant differences (p≥0.05) were identified between groups in glucocorticoid administration methods or quinolone antibiotic usage (Table 2).

Table 2
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Table 2. No statistically significant intergroup differences were observed in quinolone utilization rates (p ≥ 0.05) or systemic glucocorticoid administration patterns (p≥0.05).

3.3 Laboratory findings in AECOPD patients

Laboratory parameters of all enrolled patients were analyzed. No significant differences were observed between the depression and control groups in routine blood tests, coagulation profiles, or other biochemical markers. Hepatic and renal function tests revealed statistically significant intergroup differences in sodium levels and aspartate aminotransferase (AST) (p < 0.05), with the depression group demonstrating elevated calcium ion concentrations and lower AST values compared to controls (Table 3).

Table 3
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Table 3. The depression group exhibited significantly lower aspartate aminotransferase (AST) levels compared to the control group (p < 0.05).

3.4 Clinical characteristics of AECOPD patients with varying depression severity

Patients with AECOPD and comorbid depression (PHQ-9 score >4) were stratified into mild (86 cases) and moderate-to-severe subgroups (27 cases), with the latter combining moderate and severe categories due to limited sample size in the severe depression subgroup. Comparative analysis revealed significant differences (p < 0.05) between subgroups in sex distribution, daily cigarette consumption, and length of hospital stay. The moderate-to-severe depression subgroup exhibited a higher proportion of female patients, prolonged hospitalization, and reduced daily cigarette intake compared to the mild depression group. No significant differences (p≥0.05) were observed in age, BMI, educational attainment, comorbidities, mMRC grades, or QOL scores between subgroups (Table 4).

Table 4
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Table 4. The moderate-to-severe depression subgroup demonstrated: significantly prolonged hospitalization duration, reduced daily cigarette consumption, higher proportion of female patients, compared to the mild depression group (p < 0.05 for all comparisons).

3.5 Medication profiles of AECOPD patients with varying depression severity

Significant differences in glucocorticoid dosage were observed between the mild and moderate-to-severe depression subgroups(p<0.05), with the moderate-to-severe subgroup demonstrating higher glucocorticoid utilization. No statistically significant differences (p≥0.05) were identified between subgroups in quinolone antibiotic or theophyllines administration patterns (Table 5).

Table 5
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Table 5. Significant intergroup disparities were observed in glucocorticoid administration methods (p < 0.05).

3.6 Laboratory findings in AECOPD patients with varying depression severity

Laboratory investigations including routine blood tests, coagulation profiles, and hepatic/renal function assessments were performed across depression severity subgroups. Analytical results demonstrated marginally lower aspartate aminotransferase (AST) levels and calcium ion concentrations in the mild depression subgroup compared to the moderate-to-severe subgroup. However, no statistically significant differences (p>0.05) were observed between subgroups in routine blood parameters, coagulation indices, renal function markers, or other hepatic/electrolyte profiles (Table 6).

Table 6
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Table 6. The moderate-to-severe depression subgroup exhibited significantly higher aspartate aminotransferase (AST) levels compared to the mild depression subgroup (p < 0.05).

4 Discussion

This study found a high depression prevalence (42.01%) in AECOPD patients. This rate is 1.6-fold higher than the 26% pooled estimate from a meta-analysis of 41 COPD studies (15) and exceeds the 31% reported in a recent Beijing inpatient cohort (16). Female sex, long smoking history, clinical severity (mMRC), stigma (SIS scores), reduced QOL, and theophylline use were significantly associated with depression. These associations echo the prospective data of Huang et al. (17), who showed that baseline PHQ-9≥10 doubles the risk of subsequent exacerbations. Severity subgroup analyses revealed heterogeneity in sex distribution, glucocorticoid use, daily cigarette consumption, and hospitalization duration. The 2-day increase in median stay aligns with the +1.3-day prolongation reported by Blakemore et al. (18) in depressed COPD patients managed in primary care. The management of more complex cases, particularly treatment-resistant depression (TRD), is recognized as a clinical priority in the GOLD 2025 strategy document (19). This prevalence is higher than in the general population and may be linked to acute physiological stress (e.g., hypoxia, inflammation) and psychological burden (e.g., isolation, disease fear). The management of more complex cases, particularly treatment-resistant depression (TRD) — defined as an inadequate response to at least two trials of antidepressant therapy — poses a significant clinical challenge, as highlighted in recent national consensus guidelines and epidemiological reviews (20, 21).

Female sex as a risk factor aligns with prior research (22). Explanations include: Socioeconomic Burden: Recurrent AECOPD costs and COPD disability disproportionately affect women. Accelerated Physical Decline: Faster age-related decline may lead to earlier workforce loss and helplessness. Seasonal Synchronicity: AECOPD peaks in autumn/winter coincide with seasonal affective disorder (23), potentially amplifying symptoms in women. Symptom Sensitivity: Women show greater symptom awareness (24), worsening anxiety during exacerbations. Social Role Stress: Disease progression impeding multifaceted societal roles increases distress. Hormonal Fluctuations: Hormonal variations (menstrual cycle, menopause) may increase depression vulnerability (25, 26).

A significant link between prolonged smoking and depression highlights complex interactions. Nicotine dependence may dysregulate dopaminergic reward pathways (27, 28), inducing transient pleasure but elevating depression risk chronically. Smoking also induces systemic inflammation (29) (e.g., IL-6, TNF-α), potentially disrupting neurotransmitter balance via the gut-lung-brain axis (30), worsening mood.

Theophylline use correlated with depression risk (31). While effective for ventilation, its CNS stimulant properties (32) may contribute to neuropsychiatric issues. Phosphodiesterase inhibition increases cAMP for bronchodilation but may concurrently cause CNS hyperexcitability and neurotransmitter imbalance, increasing depression susceptibility (33). For patients exhibiting treatment resistance, augmentation strategies with agents acting on different neurotransmitter systems, such as cariprazine (a D3/D2 and serotonergic modulator), have shown promise in other treatment-resistant affective disorders (34) and could represent a novel therapeutic avenue worthy of exploration in this comorbid population.

Subgroup analyses showed two inverse associations in moderate-to-severe depression: reduced daily cigarette consumption and longer hospitalization. This paradox may reflect complex pathophysiology. Smoking reduction aligns with the Illness Perception-Behavior Modification Model (35), where patients reduce smoking recognizing symptom synergy. However, nicotine withdrawal symptoms (e.g., anxiety) (36) may worsen depression (37), creating a vicious cycle.

The glucocorticoid use disparity is notable. While effective for inflammation and respiratory function, their neuropsychiatric side effects (e.g., mood instability) are documented, especially with high-dose/long regimens (38). This necessitates cautious optimization in patients with moderate-to-severe depression. Future studies should balance anti-inflammatory efficacy with psychiatric safety.

This study first reveals in AECOPD patients the significant predictive roles of perceived stigma (SIS) and QOL in depression. Heightened stigma may reduce care-seeking (39), compromising treatment. Diminished QOL reflects physical and psychosocial impairment. Integrating psychological interventions (e.g., cognitive behavioral therapy, stigma reduction) into AECOPD management is crucial to disrupt the somatic-psychological distress cycle. The potential of CBT-based digital tools to support the embodied reintegration following pharmacologically induced plasticity, as suggested in esketamine research (40), points towards a truly multimodal and personalized approach to care.

While overlaps exist with prior AECOPD insomnia research (e.g., female sex, severity), depression shows stronger links to psychosocial factors (stigma, QOL) and specific pharmacotherapy (theophyllines), whereas sleep disturbances correlate more with nocturnal symptoms (13). This divergence suggests tailored approaches: prioritize psychosocial support for depression and optimized symptom control/oxygen therapy for sleep.

This study has several limitations. Although the total sample size (n=269) was sufficient for primary comparisons, the subgroup with severe depression (n=3) was too small for reliable analysis, necessitating cautious interpretation of these results. The single-center design may limit generalizability, and residual confounding—particularly by unmeasured socioeconomic factors—cannot be excluded. Furthermore, the cross-sectional design prevents causal inference. Future large-scale prospective studies are needed for validation.

In summary, we identified multiple depression risk factors in AECOPD: female sex, smoking history, theophylline use, disease severity, stigma, and impaired QOL. Severity subgroup analyses linked sex, glucocorticoid use, daily cigarette consumption, and hospitalization duration to aggravated depression. To validate these findings, our team plans multicenter studies with expanded samples and follow-up to evaluate characteristics and identify precise interventions, optimizing clinical practice. The insights from recent research on TRD management (20, 21), novel pharmacological mechanisms (34), and the interplay between neuropharmacological action and psychological change (40) provide valuable frameworks for developing these future interventions.

5 Conclusions

This study demonstrates that patients with AECOPD who are female, receive theophylline therapy, have more severe disease, report higher levels of perceived stigma, or have poorer quality of life are at a significantly increased risk of developing depression. Furthermore, depression severity is associated with female sex, prolonged hospitalization, and glucocorticoid use. However, it should be noted that certain subgroup analyses may be limited by small sample sizes, and these findings should be interpreted with caution until validated in larger cohorts. Optimizing AECOPD treatment to alleviate clinical symptoms may help reduce the incidence of comorbid depression. These results highlight the importance of incorporating psychosocial assessments and tailored interventions into standard COPD care to address the combined burden of respiratory and depressive illness.

Data availability statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Ethics statement

The studies involving humans were approved by the Ethics Committee of Chaohu Hospital Affiliated with Anhui Medical University (Approval No.KYXM-202309-005). The studies were conducted in accordance with the local legislation and institutional requirements. Written informed consent for participation in this study was provided by the participants’ legal guardians/next of kin.

Author contributions

YC: Funding acquisition, Writing – original draft. QG: Software, Writing – original draft. HJ: Data curation, Funding acquisition, Writing – original draft. KQ: Investigation, Writing – review & editing. HZ: Funding acquisition, Writing – review & editing.

Funding

The author(s) declare financial support was received for the research and/or publication of this article. This work was supported by the Postgraduate Research and Practice Innovation Program of Anhui Medical University (Grant No. YJS20230201), the Postgraduate Research and Practice Innovation Program of Anhui Medical University (Grant No. YJS20240108) and Health research project of Anhui Province(Grant No. AHWJ2024Aa20332).

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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The author(s) declare that no Generative AI was used in the creation of this manuscript.

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References

1. Vogelmeier CF, Criner GJ, Martinez FJ, Anzueto A, Barnes PJ, Bourbeau J, et al. Global strategy for the diagnosis, management, and prevention of chronic obstructive lung disease 2017 report: GOLD executive summary. Eur Respir J. (2017) 49:1700214. doi: 10.1183/13993003.00214-2017

PubMed Abstract | Crossref Full Text | Google Scholar

2. Guan Z, Li H, Liu R, Cai C, Liu Y, Li J, et al. Artificial intelligence in diabetes management: Advancements, opportunities, and challenges. Cell Rep Med. (2023) 4:101213. doi: 10.1016/j.xcrm.2023.101213

PubMed Abstract | Crossref Full Text | Google Scholar

3. General Directorate of Health Information Systems. (2024). Health statistics yearbook 2022 (Publication No. 1280). Ministry of Health. Available online at: https://ohsad.org/wp-content/uploads/2024/05/Saglik-Istatistikleri-Yilligi-2022-Ingilizce.pdf.

Google Scholar

4. Murphy MJ and Peterson MJ. Sleep disturbances in depression. Sleep Med Clinics. (2015) 10:17–23. doi: 10.1016/j.jsmc.2014.11.009

PubMed Abstract | Crossref Full Text | Google Scholar

5. Yohannes AM, Baldwin RC, and Connolly MJ. Depression and anxiety in elderly outpatients with chronic obstructive pulmonary disease: prevalence, and validation of the BASDEC screening questionnaire. Int J geriatric Psychiatry. (2000) 15:1090–6. doi: 10.1002/1099-1166(200012)15:12<1090::aid-gps249>3.0.co;2-l

PubMed Abstract | Crossref Full Text | Google Scholar

6. Kunik ME, Roundy K, Veazey C, Souchek J, Richardson P, Wray NP, et al. Surprisingly high prevalence of anxiety and depression in chronic breathing disorders. Chest. (2005) 127:1205–11. doi: 10.1378/chest.127.4.1205

PubMed Abstract | Crossref Full Text | Google Scholar

7. Phan T, Carter O, Waterer G, Chung LP, Hawkins M, Rudd C, et al. Determinants for concomitant anxiety and depression in people living with chronic obstructive pulmonary disease. J psychosomatic Res. (2019) 120:60–5. doi: 10.1016/j.jpsychores.2019.03.004

PubMed Abstract | Crossref Full Text | Google Scholar

8. Biswas D, Mukherjee S, Chakroborty R, Chatterjee S, Rath S, Das R, et al. Occurrence of Anxiety and Depression among St able COPD Patients and its Impact on Functional Capability. J Clin Diagn research: JCDR. (2017) 11:OC24–7. doi: 10.7860/JCDR/2017/24203.9393

PubMed Abstract | Crossref Full Text | Google Scholar

9. Maurer J, Rebbapragada V, Borson S, Goldstein R, Kunik ME, Yohannes AM, et al. Anxiety and depression in COPD: current understanding, unanswered questions, and research needs. Chest. (2008) 134:43S–56S. doi: 10.1378/chest.08-0342

PubMed Abstract | Crossref Full Text | Google Scholar

10. Yohannes AM, Willgoss TG, Baldwin RC, and Connolly MJ. Depression and anxiety in chronic heart failure and chronic obstructive pulmonary disease: prevalence, relevance, clinical implications and management principles. Int J geriatric Psychiatry. (2010) 25:1209–21. doi: 10.1002/gps.2463

PubMed Abstract | Crossref Full Text | Google Scholar

11. Panagioti M, Scott C, Blakemore A, and Coventry PA. Overview of the prevalence, impact, and management of depression and anxiety in chronic obstructive pulmonary disease. Int J chronic obstructive pulmonary Dis. (2014) 9:1289–306. doi: 10.2147/COPD.S72073

PubMed Abstract | Crossref Full Text | Google Scholar

12. Wang R, Nie S, and Li DQ. Factors influencing anxiety and depression in COPD patients and their correlation with quality of life and sleep quality. Journal of Aerospace Medicine. (2024) 35:560–3.

Google Scholar

13. Corlateanu A, Covantsev S, Iasabash O, Lupu L, Avadanii M, and Siafakas N. Chronic obstructive pulmonary disease and depression-the vicious mental cycle. Healthcare (Basel). (2025) 13:1699. doi: 10.3390/healthcare13141699

PubMed Abstract | Crossref Full Text | Google Scholar

14. Gao Q and Zhu H. Investigating the risk factors for the coexistence of insomnia and its exacerbation in AECOPD. Respir Med. (2025) 238:107987. doi: 10.1016/j.rmed.2025.107987

PubMed Abstract | Crossref Full Text | Google Scholar

15. Salte K, Titlestad I, and Halling A. Depression is associated with poor prognosis in patients with chronic obstructive pulmonary disease-a systematic review. Dan Med J. (2015) 62:A5137.

PubMed Abstract | Google Scholar

16. Feng L, Li J, Lv X, Chu S, Li C, Zhang R, et al. Temporal trends in anxiety and depression prevalence among patients hospitalized for AECOPD in Beijing, 2004-2020. BMC Psychiatry. (2022) 22:688. doi: 10.1186/s12890-022-01934-y

PubMed Abstract | Crossref Full Text | Google Scholar

17. Huang J, Bian Y, Zhao Y, Jin Z, Liu L, and Li G. Impact of depression and anxiety on COPD acute exacerbations: prospective cohort. J Affect Disord. (2021) 281:147–52. doi: 10.1016/j.jad.2020.12.030

PubMed Abstract | Crossref Full Text | Google Scholar

18. Blakemore A, Dickens C, Chew-Graham CA, Afzal CW, Tomenson B, Coventry PA, et al. Depression predicts emergency care use in COPD: primary-care cohort. Int J Chron Obstruct Pulmon Dis. (2019) 14:1343–53. doi: 10.2147/COPD.S179109

PubMed Abstract | Crossref Full Text | Google Scholar

19. Global Initiative for Chronic Obstructive Lung Disease. Global initiative for chronic obstructive lung disease. In: Global strategy for the diagnosis, management, and prevention of COPD 2025 report. (2024)

Google Scholar

20. Maina G, Adami M, Ascione G, Bondi E, De Berardis D, Delmonte D, et al. Nationwide consensus on the clinical management of treatment−resistant depression in Italy: a Delphi panel. Ann Gen Psychiatry. (2023) 22:48. doi: 10.1186/s12991-023-00478-7

PubMed Abstract | Crossref Full Text | Google Scholar

21. Fiorillo A, Demyttenaere K, Martiadis V, and Martinotti G. Editorial: Treatment-resistant depression (TRD): epidemiology, clinic, burden and treatment. Front Psychiatry. (2025) 16:1588902. doi: 10.3389/fpsyt.2025.1588902

PubMed Abstract | Crossref Full Text | Google Scholar

22. Albert KM and Newhouse PA. Estrogen, stress, and depression: cognitive and biological interactions. Annu Rev Clin Psychol. (2019) 15:399–423. doi: 10.1146/annurev-clinpsy-050718-095557

PubMed Abstract | Crossref Full Text | Google Scholar

23. Monteleone P and Maj M. The circadian basis of mood disorders: recent developments and treatment implications. Eur neuropsychopharmacology: J Eur Coll Neuropsychopharmacol. (2008) 18:701–11. doi: 10.1016/j.euroneuro.2008.06.007

PubMed Abstract | Crossref Full Text | Google Scholar

24. Bangasser DA and Cuarenta A. Sex differences in anxiety and depression: circuits and mechanisms. Nat Rev Neurosci. (2021) 22:674–84. doi: 10.1038/s41583-021-00513-0

PubMed Abstract | Crossref Full Text | Google Scholar

25. Hart T, Hoffman JM, Pretz C, Kennedy R, Clark AN, and Brenner LA. A longitudinal study of major and minor depression following traumatic brain injury. Arch Phys Med Rehabil. (2012) 93:1343–9. doi: 10.1016/j.apmr.2012.03.036

PubMed Abstract | Crossref Full Text | Google Scholar

26. Lialy HE, Mohamed MA, AbdAllatif LA, Khalid M, and Elhelbawy A. Effects of different physiotherapy modalities on insomnia and depression in perimenopausal, menopausal, and post-menopausal women: a systematic review. BMC women’s Health. (2023) 23:363. doi: 10.1186/s12905-023-02515-9

PubMed Abstract | Crossref Full Text | Google Scholar

27. Di X, Yan J, Zhao Y, Chang Y, and Zhao B. L-theanine inhibits nicotine-induced dependence via regulation of the nicotine acetylcholine receptor-dopamine reward pathway. Sci China. Life Sci. (2012) 55:1064–74. doi: 10.1007/s11427-012-4401-0

PubMed Abstract | Crossref Full Text | Google Scholar

28. Vieyra-Reyes P, Venebra-Muñoz A, Rivas-Santiago B, and García-García F. Acción de la nicotina como antidepresivo y regulador del sueño en sujetos deprimidos [Nicotine as an antidepressant and regulator of sleep in subjects with depression. Rev neurologia. (2009) 49:661–7.

Google Scholar

29. Zhang W, Lin H, Zou M, Yuan Q, Huang Z, Pan X, et al. Nicotine in inflammatory diseases: anti-inflammatory and pro-inflammatory effects. Front Immunol. (2022) 13:826889. doi: 10.3389/fimmu.2022.826889

PubMed Abstract | Crossref Full Text | Google Scholar

30. Sorboni SG, Moghaddam HS, Jafarzadeh-Esfehani R, and Soleimanpour S. A comprehensive review on the role of the gut microbiome in human neurological disorders. Clin Microbiol Rev. (2022) 35:e0033820. doi: 10.1128/CMR.00338-20

PubMed Abstract | Crossref Full Text | Google Scholar

31. Murphy MB, Dillon A, and Fitzgerald MX. Theophylline and depression. Br Med J. (1980) 281:1322. doi: 10.1136/bmj.281.6251.1322

PubMed Abstract | Crossref Full Text | Google Scholar

32. Hall RC, Beresford TP, Stickney SK, Nasdahl CS, and Coleman JH. Psychiatric reactions produced by respiratory drugs. Psychosomatics. (1985) 26:605–16. doi: 10.1016/S0033-3182(85)72823-X

PubMed Abstract | Crossref Full Text | Google Scholar

33. Faro D, Boekhoff I, Gudermann T, and Breit A. Physiological temperature changes fine-tune β2- adrenergic receptor-induced cytosolic cAMP accumulation. Mol Pharmacol. (2021) 100:203–16. doi: 10.1124/molpharm.121.000309

PubMed Abstract | Crossref Full Text | Google Scholar

34. Martiadis V, Pessina E, Martini A, Raffone F, Cattaneo CI, De Berardis D, et al. Serotonin reuptake inhibitors augmentation with cariprazine in patients with treatment−Resistant obsessive−Compulsive disorder: A retrospective observational study. CNS Spectrums. (2024) 12:1–4. doi: 10.1017/S1092852924000348

PubMed Abstract | Crossref Full Text | Google Scholar

35. Joshi S, Dhungana RR, and Subba UK. Illness perception and depressive symptoms among persons with type 2 diabetes mellitus: an analytical cross-sectional study in clinical settings in Nepal. J Diabetes Res. (2015) 2015:908374. doi: 10.1155/2015/908374

PubMed Abstract | Crossref Full Text | Google Scholar

36. Prochaska JJ and Benowitz NL. Current advances in research in treatment and recovery: Nicotine addiction. Sci Adv. (2019) , 5:eaay9763. doi: 10.1126/sciadv.aay9763

PubMed Abstract | Crossref Full Text | Google Scholar

37. Wang S, Wang C, Yu Z, Wu C, Peng D, Liu X, et al. Agarwood essential oil ameliorates restrain stress-induced anxiety and depression by inhibiting HPA axis hyperactivity. Int J Mol Sci. (2018) 19:3468. doi: 10.3390/ijms19113468

PubMed Abstract | Crossref Full Text | Google Scholar

38. Cornic F and Rousset I. Troubles neuropsychiatriques liés aux corticoïdes [Glucocorticoids induced neuropsychiatric disorders. La Rev du praticien. (2008) 58:469–75.

Google Scholar

39. Link BG, Struening EL, Rahav M, Phelan JC, and Nuttbrock L. On stigma and its consequences: evidence from a longitudinal study of men with dual diagnoses of mental illness and substance abuse. J Health Soc Behav. (1997) 38:177–90. doi: 10.2307/2955424

PubMed Abstract | Crossref Full Text | Google Scholar

40. Sarasso P, Billeci M, Di Petta G, Martiadis V, Raffone F, and Ronga I. Disembodiment and affective resonances in esketamine treatment of depersonalized depression subtype: two case studies. Psychopathology. (2024) 57:480–91. doi: 10.1159/000539714

PubMed Abstract | Crossref Full Text | Google Scholar

Keywords: AECOPD, depression, risk factors, quality of life, stigma

Citation: Chen Y, Gao Q, Jia H, Qian K and Zhu H (2025) Impact of comorbid depression on quality of life and disease progression in chronic obstructive pulmonary disease: a correlational analysis. Front. Psychiatry 16:1667902. doi: 10.3389/fpsyt.2025.1667902

Received: 18 July 2025; Accepted: 18 September 2025;
Published: 08 October 2025.

Edited by:

Vassilis Martiadis, Asl Napoli 1 Centro, Italy

Reviewed by:

Alexandru Corlateanu, Nicolae Testemiţanu State University of Medicine and Pharmacy, Moldova
Fabiola Raffone, Asl Napoli 1 Centro, Italy

Copyright © 2025 Chen, Gao, Jia, Qian and Zhu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Hongbin Zhu, Wmh1aG9uZ2Jpbjc4OEAxNjMuY29t

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