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Respiratory disease in people with major depressive disorder: A systematic review and Meta-analysis

Published online by Cambridge University Press:  05 February 2025

Ana Jiménez-Peinado
Affiliation:
Maimonides Biomedical Research Institute of Cordoba (IMIBIC), Córdoba, Spain Reina Sofia University Hospital, Córdoba, Spain Department of Morphological and Sociosanitary Science, University of Córdoba, Córdoba, Spain
David Laguna-Muñoz
Affiliation:
Maimonides Biomedical Research Institute of Cordoba (IMIBIC), Córdoba, Spain Reina Sofia University Hospital, Córdoba, Spain Department of Morphological and Sociosanitary Science, University of Córdoba, Córdoba, Spain
María José Jaén-Moreno*
Affiliation:
Maimonides Biomedical Research Institute of Cordoba (IMIBIC), Córdoba, Spain Reina Sofia University Hospital, Córdoba, Spain Department of Morphological and Sociosanitary Science, University of Córdoba, Córdoba, Spain
Cristina Camacho-Rodríguez
Affiliation:
Maimonides Biomedical Research Institute of Cordoba (IMIBIC), Córdoba, Spain
Gloria Isabel del Pozo
Affiliation:
Maimonides Biomedical Research Institute of Cordoba (IMIBIC), Córdoba, Spain Reina Sofia University Hospital, Córdoba, Spain Department of Morphological and Sociosanitary Science, University of Córdoba, Córdoba, Spain
Eduard Vieta*
Affiliation:
Department of Medicine, School of Medicine and Health Sciences, University of Barcelona (UB), Barcelona, Catalonia, Spain Bipolar and Depressive Disorders Unit, Hospìtal Clinic, Barcelona, Catalonia, Spain Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Catalonia, Spain Institute of Neurosciences (UBNeuro) Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
Javier Caballero-Villarraso
Affiliation:
Maimonides Biomedical Research Institute of Cordoba (IMIBIC), Córdoba, Spain Reina Sofia University Hospital, Córdoba, Spain Department of Biochemistry and Molecular Biology, UGC Clinical Analyses, University of Córdoba, Córdoba, Spain
Fernando Rico-Villademoros
Affiliation:
Instituto de Neurociencias, Universidad de Granada, Granada, Spain
Fernando Sarramea
Affiliation:
Maimonides Biomedical Research Institute of Cordoba (IMIBIC), Córdoba, Spain Reina Sofia University Hospital, Córdoba, Spain Department of Morphological and Sociosanitary Science, University of Córdoba, Córdoba, Spain Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
*
Corresponding authors: María José Jaén-Moreno and Eduard Vieta; Emails:[email protected];[email protected]
Corresponding authors: María José Jaén-Moreno and Eduard Vieta; Emails:[email protected];[email protected]

Abstract

Background

Living with major depressive disorder (MDD) reduces life expectancy, with respiratory disease being a significant threat. However, evidence on respiratory disease in this population has not yet been meta-analyzed.

Methods

This meta-analysis examines respiratory disease prevalence and odds ratio (OR) in patients with MDD and treatment resistant depression (TRD). A systematic literature search was conducted, with a snowball search of reference and citation lists. Inclusion criteria covered studies in MDD and TRD patients with confirmed diagnoses of respiratory diseases (asthma, chronic obstructive pulmonary disease [COPD], pneumonia, lung cancer, and tuberculosis), comparing with a control group when possible.

Results

From 4,138 retrieved articles, 15 (including 476,927 individuals with MDD, 50,680 with TRD, and 1,108,979 control group) met the inclusion criteria. In MDD patients, COPD prevalence was 9.0% (95% CI: 3.8–19.6%), asthma 8.6% (95% CI: 5.7–12.8%), and pneumonia 2.5% (95% CI: 2.2–2.9%). In TRD patients, COPD prevalence was 9.9% (95% CI: 4.2–21.9%) and asthma 10.9% (95% CI: 10.7–11.2%), but meta-analysis limited to those diseases showed no significant relative risk differences. Compared to the general population, individuals with MDD had significantly higher rates of COPD (OR 1.79, 95% CI: 1.49–2.16), even higher in younger populations (1.85 [95% CI: 1.74–1.97]) and more prevalent in women.

Conclusions

This first meta-analysis on this topic shows that MDD is associated with an increased risk of respiratory illness compared to the general population. The prevalence of asthma doubles the mean described in the general population worldwide, and in COPD, women and younger people are at particular risk. Prevention policies are urgently needed.

Type
Review/Meta-analysis
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2025. Published by Cambridge University Press on behalf of European Psychiatric Association

Introduction

Major depressive disorder (MDD) is a common disease, ranking as the third leading cause of global disease burden [1]. Nearly one in five people will experience MDD in their lifetime [Reference Bromet, Andrade, Hwang, Sampson, Alonso and de Girolamo2], and the one-year prevalence is very similar in high- (5.5%), middle-, and low-income countries (5.9%) [Reference Vos, Allen, Arora, Barber, Bhutta and Brown3] In addition to its impact on a person’s daily life and the huge social and economic burden it poses, depression increases the risk of all-cause mortality [Reference Lee, Lee, Lee, Park and Kim4].

The link between early mortality and mental illness is an overall and transdiagnostic reality with a multidimensional origin [Reference Firth, Siddiqi, Koyanagi, Siskind, Rosenbaum and Galletly5]. Despite the high risk of suicide, the main cause of mortality in this population is preventable physical illness. It usually starts earlier and without timely diagnosis and treatment [Reference Firth, Siddiqi, Koyanagi, Siskind, Rosenbaum and Galletly5]. The gap in life expectancy with the general population keeps the same, and it is urgent to develop initiatives to understand the main risk factors [Reference Fiorillo and Sartorius6].

An increased risk of pulmonary disease has recently been described in individuals with schizophrenia and bipolar disorder [Reference Suetani, Honarparvar, Siskind, Hindley, Veronese and Vancampfort7,Reference Laguna-Muñoz, Jiménez-Peinado, Jaén-Moreno, Camacho-Rodríguez, del Pozo and Vieta8]. However, to our knowledge, this has not been meta-analyzed in individuals with MDD.

Our aim was to conduct a systematic review and meta-analysis of the five most common respiratory diseases (chronic obstructive pulmonary disease [COPD], asthma, pneumonia, lung cancer, and tuberculosis) in individuals with MDD, estimating their prevalence and odds ratio (OR) compared to the general population.

Materials and methods

We adhered to the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocol (PRISMA) [Reference Moher, Liberati, Tetzlaff, Altman and Group9] and the Meta-analysis of Observational Studies in Epidemiology (MOOSE) guidelines [Reference Stroup, Berlin, Morton, Olkin, Williamson and Rennie10]. The study was registered with PROSPERO (CRD42023470972). The MOOSE checklist is presented in Supplementary Table 1.

Information sources and searches

The search covered from inception to October 3, 2023. Two independent authors (D.L-M. and A.J-P.) searched in Pubmed, PsycINFO, and Scopus. On October 3, 2023, we extracted data using the following terms: (“major depression” OR “affective disorder” OR “mood disorder” OR “serious mental illness” OR “severe mental illness” OR “severe mental disorder”) AND (“respiratory tract diseases” OR “lung diseases” OR “asthma” OR “chronic bronchitis” OR “emphysema” OR “chronic pulmonary disease” OR “COPD” OR “chronic obstructive pulmonary disease” OR “pneumonia” OR “tuberculosis” OR “lung cancer” OR “lung neoplasms”). Moreover, our research methodology included both forward and backward reference searching: the former involved identifying articles that cited the original work post-publication, while the latter, entailed examining references or works cited within selected articles.

We included studies that: (a) focused on adult participants with a diagnosis of MDD according to established diagnostic criteria (e.g., DSM- IV [11] or ICD-10 [12]); (b) reported prevalence of respiratory disease, including asthma, COPD (including the terms chronic bronchitis and emphysema [13], pneumonia, lung cancer, or tuberculosis confirmed by means of medical diagnosis, medical records, or ICD criteria; (c) had an observational design (prospective, retrospective, or cross-sectional) and were conducted in any setting (hospital, community, or both), regardless of whether a general population control group was included; and (d) were published in an indexed, peer-reviewed journal in English.

Outcomes

The primary outcomes were the prevalence of asthma, COPD, pneumonia, lung cancer, and tuberculosis in individuals with MDD. The secondary outcome analysis also took into consideration the comparison between individuals with major depressive disorder resistant to treatment (TRD) and those without treatment resistance (non-TRD). Moreover, we determined the combined prevalence of respiratory disease across these groups. If a study that met the inclusion criteria but did not contain sufficient data for meta-analysis, we contacted the authors to request relevant data.

Data extraction

Two authors (A.J-P. and D.L-M.) extracted data using a predetermined data extraction form. The extracted information included the first author, country, setting, population, study design (median year, prospective, retrospective, cross-sectional), number of participants and their demographics (sex, mean age), smoking status, and antipsychotics or mood stabilizer use, as included in the article and the frequency of each respiratory disease.

Methodological quality appraisal

The quality of each study was assessed using the Newcastle–Ottawa Scale (NOS) [Reference Wells GS, O’Connell, Peterson, Welch, Losos and Tugwell14]. Points are assigned based on the selection process of cohorts (0–4 points), comparability of the cohorts (0–2 points), and identification of the exposures and the outcomes of research participants (0–3 points). We used a modified version for cross-sectional studies to adjust the evaluation [Reference Herzog, Álvarez-Pasquin, Díaz, Del Barrio, Estrada and Gil15]. The results are categorized as “Good” (7–9 points), “Fair” (5–6 points), and “Poor” (<5 points). Any disagreements were settled by discussing with another author (MJJ).

Statistical analyses

Statistical analysis was conducted in a sequence. First, we calculated the prevalence of each specific respiratory disease among individuals with MDD, along with the 95% CI. We then compared the prevalence of each respiratory disease among individuals with MDD versus controls where available, calculating ORs together with 95% CIs. A random- effects meta-analysis was conducted. To visualize heterogeneity, prediction intervals were included in forest plots, along with calculating the I2 statistics for each analysis. Small study effects and publication bias were assessed by visual inspection of funnel plots and using Egger’s test when appropriate (k > 10) [Reference Higgins16]. Publication bias was assessed and adjusted for with trim and fill adjusted analysis where possible. For sensitivity analyses, we calculated the subgroup differences investigating if the prevalence of each respiratory disease differed according to study design, location (Europe, North America, and Asia), and study setting. We also conducted the sensitivity analysis for the meta-analysis [Reference Higgins and Thompson17]. Likewise, the effects of potential continuous effect modifiers (mean age, median year of publication, proportion of males) were examined using meta-regression. We anticipated comparing the prevalence of respiratory diseases according to smoking status and psychotropic use, but there were insufficient data. All analyses were performed using R application [18], with packages metafor [Reference Viechtbauer19], meta [Reference Balduzzi, Rücker and Schwarzer20], and dmetar [Reference Harrer, Cuijpers, Furukawa and Ebert21].

Results

The initial database search identified 4,133 articles after excluding duplications. Additional five studies were found through the inspection of bibliographies. In total, 4,138 articles were screened at the title and abstract level. After reviewing 92 full texts, 77 were excluded with reasons (see Supplementary Table 2). Finally, 15 unique studies met the eligibility criteria. Full details of the search results are summarized in Supplementary Figure 1.

There were 476,927 individuals with MDD with a mean age of 57.4 years (range: 45.8–77.1 years). 45.0% were male (range: 31.7–97.5%). Four studies considered asthma as their outcome [Reference Lin, Szukis, Sheehan, Alphs, Menges and Lingohr-Smith22Reference Schoepf, Uppal, Potluri, Chandran and Heun25]. Fourteen studies investigated COPD [Reference Rizvi, Grima, Tan, Rotzinger, Lin and McIntyre23Reference Balogun, Omotoso, Xin, Ma, Scully and Arogundade36]. Two studies examined pneumonia [Reference Schoepf, Uppal, Potluri, Chandran and Heun25,Reference Sweer, Martin, Ladd, Miller and Karpf29]. One study considered tuberculosis as its outcome [Reference Ryu, Lee, Park, Jung and Kang24]. No studies provided data on lung cancer. Among TRD, there were 50,680 individuals with a mean age of 52.4 years (range: 45.9–58.9 years) and 35.3% male (range: 28.0–43.2%). In this population, two studies considered asthma as their outcome [Reference Lin, Szukis, Sheehan, Alphs, Menges and Lingohr-Smith22,Reference Rizvi, Grima, Tan, Rotzinger, Lin and McIntyre23] and four studies investigated COPD [Reference Rizvi, Grima, Tan, Rotzinger, Lin and McIntyre23,Reference Pilon, Joshi, Sheehan, Zichlin, Zuckerman and Lefebvre26,Reference Sharman Moser, Chodick, Gelerstein, Barit Ben David, Shalev and Stein-Reisner27,Reference Olfson, Amos, Benson, McRae and Marcus30]. Details of the included studies and participants are presented in Table 1 and Supplementary Table 3.

Table 1. Characteristics of included studies

One study was conducted in the 1980s [Reference Sweer, Martin, Ladd, Miller and Karpf29], seven studies in the 2000s [Reference Ryu, Lee, Park, Jung and Kang24,Reference Schoepf, Uppal, Potluri, Chandran and Heun25,Reference DeWaters, Chansard, Anzueto, Pugh and Mortensen28,Reference Oh, Choi, Kim, Kim and Cho31Reference Davydow, Ribe, Pedersen, Vestergaard and Fenger-Grøn33,Reference Balogun, Omotoso, Xin, Ma, Scully and Arogundade36,Reference Chen, Huang, Chang, Pan, Su and Yang37], six studies in the 2010s [Reference Lin, Szukis, Sheehan, Alphs, Menges and Lingohr-Smith22,Reference Rizvi, Grima, Tan, Rotzinger, Lin and McIntyre23,Reference Pilon, Joshi, Sheehan, Zichlin, Zuckerman and Lefebvre26,Reference Olfson, Amos, Benson, McRae and Marcus30,Reference Chen, Chan, Yeh and Pan34,Reference So-Armah, Gupta, Kundu, Stewart, Goulet and Butt35], and one study in the 2020s [Reference Sharman Moser, Chodick, Gelerstein, Barit Ben David, Shalev and Stein-Reisner27].

One study was prospective [Reference So-Armah, Gupta, Kundu, Stewart, Goulet and Butt35], while the remaining 14 were retrospective cohort studies. Five studies were conducted in Asia [Reference Ryu, Lee, Park, Jung and Kang24,Reference Sharman Moser, Chodick, Gelerstein, Barit Ben David, Shalev and Stein-Reisner27,Reference Oh, Choi, Kim, Kim and Cho31,Reference Shen, Lin, Liao, Wei, Sung and Kao32,Reference Chen, Chan, Yeh and Pan34], two studies in Europe [Reference Schoepf, Uppal, Potluri, Chandran and Heun25,Reference Davydow, Ribe, Pedersen, Vestergaard and Fenger-Grøn33], and eight in North America [Reference Lin, Szukis, Sheehan, Alphs, Menges and Lingohr-Smith22,Reference Pilon, Joshi, Sheehan, Zichlin, Zuckerman and Lefebvre26,Reference DeWaters, Chansard, Anzueto, Pugh and Mortensen28Reference Olfson, Amos, Benson, McRae and Marcus30,Reference So-Armah, Gupta, Kundu, Stewart, Goulet and Butt35,Reference Balogun, Omotoso, Xin, Ma, Scully and Arogundade36].

Two studies included participants from the community [Reference Rizvi, Grima, Tan, Rotzinger, Lin and McIntyre23,Reference Ryu, Lee, Park, Jung and Kang24], six from patients admitted to a hospital [Reference Lin, Szukis, Sheehan, Alphs, Menges and Lingohr-Smith22,Reference Schoepf, Uppal, Potluri, Chandran and Heun25,Reference DeWaters, Chansard, Anzueto, Pugh and Mortensen28,Reference Sweer, Martin, Ladd, Miller and Karpf29,Reference Davydow, Ribe, Pedersen, Vestergaard and Fenger-Grøn33,Reference Balogun, Omotoso, Xin, Ma, Scully and Arogundade36], and six from both community and patients admitted to hospital settings [Reference Pilon, Joshi, Sheehan, Zichlin, Zuckerman and Lefebvre26,Reference Sharman Moser, Chodick, Gelerstein, Barit Ben David, Shalev and Stein-Reisner27,Reference Olfson, Amos, Benson, McRae and Marcus30,Reference Shen, Lin, Liao, Wei, Sung and Kao32,Reference Chen, Chan, Yeh and Pan34,Reference So-Armah, Gupta, Kundu, Stewart, Goulet and Butt35].

Full details of the meta-analyses of the prevalence of respiratory diseases are presented in Table 2 and Figure 1. The funnel plot for COPD is presented in Supplementary Figure 2. The combined prevalence of respiratory disease in MDD was 6.9% (95% CI: 3.6–13.0%). There were sufficient data to meta-analyze for three conditions. Across four studies [Reference Lin, Szukis, Sheehan, Alphs, Menges and Lingohr-Smith22Reference Schoepf, Uppal, Potluri, Chandran and Heun25] with a total of 252,945 individuals with MDD, the prevalence of asthma was 8.6% (95% CI: 5.7–12.8%). The prevalence of COPD in 386,795 individuals with MDD was 9.0% (95% CI: 3.8–19.6%) among 14 studies [Reference Rizvi, Grima, Tan, Rotzinger, Lin and McIntyre23Reference Balogun, Omotoso, Xin, Ma, Scully and Arogundade36]. The prevalence of pneumonia in 9,704 individuals with MDD was 2.5% (95% CI: 2.2–2.9%) among 2 studies [Reference Schoepf, Uppal, Potluri, Chandran and Heun25,Reference Sweer, Martin, Ladd, Miller and Karpf29]. Unfortunately, there was only one study of tuberculosis, making meta-analysis impossible. In Ryu et al. study, involving 37,554 individuals with MDD, the prevalence of tuberculosis was 0.4%.

Table 2. Prevalence of respiratory disease in people with major depressive disorder

CI, confidence interval; COPD, chronic obstructive pulmonary disease

Figure 1. Forest plot for prevalence of respiratory disease in people with major depressive disorder.

After adjusting for potential publication bias, the prevalence was slightly higher in COPD (9.6%, 95% CI: 3.0–27.2%) compared to the rest of the included diseases. After excluding outliers, the heterogeneity markedly decreased.

With respect to the TRD group, full details of the meta-analyses of the prevalence of respiratory diseases are presented in Supplementary Table 4 and Supplementary Figure 3. With a total of 50,680 individuals, the combined prevalence of respiratory disease in TRD was 9.9% (95% CI: 5.6–17.0%). There were sufficient data to meta-analyze two conditions. Across two studies [Reference Lin, Szukis, Sheehan, Alphs, Menges and Lingohr-Smith22,Reference Rizvi, Grima, Tan, Rotzinger, Lin and McIntyre23] with a total of 45,390 individuals with TRD, the prevalence of asthma was 10.9% (95% CI: 10.7–11.2%). The prevalence of COPD in 5,614 individuals with TRD was 9.9% (95% CI: 4.2–21.9%) among four studies [Reference Rizvi, Grima, Tan, Rotzinger, Lin and McIntyre23Reference Balogun, Omotoso, Xin, Ma, Scully and Arogundade36].

Full details of the comparative meta-analyses are summarized in Table 3 and Figure 2. The funnel plot for COPD is presented in Supplementary Figure 4. There were sufficient data to meta-analyze two conditions: asthma (two studies [Reference Ryu, Lee, Park, Jung and Kang24,Reference Schoepf, Uppal, Potluri, Chandran and Heun25]) and COPD (eight studies [Reference Ryu, Lee, Park, Jung and Kang24Reference Pilon, Joshi, Sheehan, Zichlin, Zuckerman and Lefebvre26,Reference DeWaters, Chansard, Anzueto, Pugh and Mortensen28,Reference Shen, Lin, Liao, Wei, Sung and Kao32,Reference Davydow, Ribe, Pedersen, Vestergaard and Fenger-Grøn33,Reference So-Armah, Gupta, Kundu, Stewart, Goulet and Butt35,Reference Balogun, Omotoso, Xin, Ma, Scully and Arogundade36]). In those respiratory conditions, we found that individuals with MDD had higher odds of having respiratory diseases – asthma (OR 1.74, 95% CI: 0.14–21.37) and COPD (OR 1.79, 95% CI: 1.49–2.16) with no significant differences in asthma compared to individuals without MDD. After adjusting for potential publication bias using the trim and fill adjustment and after excluding outliers, the OR for COPD was still significantly higher in patients with MDD, with a value of 1.79 (79% increased risk, 95% CI = [1.49–2.15]), with more precise confidence intervals (Supplementary Figure 5). Unfortunately, there was only one tuberculosis and one pneumonia studies, being impossible to set a comparative meta-analysis. In the former study [Reference Ryu, Lee, Park, Jung and Kang24], the OR was 2.02 (95% CI: 1.76–2.33). In the later study [Reference Schoepf, Uppal, Potluri, Chandran and Heun25], the OR was 1.41 (95% CI: 1.18–1.70).

Table 3. Odds Ratio of respiratory disease in people with major depressive disorder compared with controls

CI, confidence interval; COPD, chronic obstructive pulmonary disease

Figure 2. Forest plot for Odds Ratio of respiratory disease in people with major depressive disorder compared with controls.

We obtained sufficient data to perform subgroup analyses for the prevalence of COPD and asthma among individuals with MDD. Full details of the subgroup analyses of the prevalence of respiratory diseases are summarized in Supplementary Tables 5 and 6. There were no differences in the prevalence of asthma between sex, age, location, or setting. In the case of COPD, there were differences between locations. The prevalence of COPD was statistically higher in North America (16.3%, 95% CI: 7.3–32.6%) and Europe (15.5%, 95% CI: 4.2–43.7%) compared to Asia (3.0%, 95% CI: 0.6–14.1%). There were also statistically significant differences between inpatient (20.1, 95% CI: 7.4–44.4%) compared to a mixed population of inpatients and outpatients (12.9%, 95% CI: 7.0–22.4%) and outpatient group (1.0%, 95% CI: 0.2–5.4%). In meta-regression, the prevalence of COPD was higher when the percentage of women was greater (Supplementary Figure 6). The analysis revealed an adjusted sex prevalence of COPD was 9.0% (95% CI: 4.3–17.8%). There were no differences between age groups.

We found sufficient data to conduct subgroup analyses for the comparative meta-analyses for COPD (Supplementary Table 7). The likelihood ratio of COPD was greater for people with MDD in retrospective studies (OR 1.78, 95% CI: 1.43–2.21), North American studies (OR 1.64, 95% CI: 1.17–2.31), inpatient setting (OR 1.7, 95% CI: 1.10–2.80), and both inpatient and community setting (OR 1.96, 95% CI: 1.43–2.69). In the meta-regression, younger patients have an increased risk of developing COPD compared to older people (Supplementary Figure 7). The adjusted age OR for COPD was calculated at 1.85 (95% CI: 1.74–1.97). No differences were found between the sexes.

We also obtained datasets that allow for a sub-analysis, focusing on the interplay between TRD and non-TRD in asthma [Reference Lin, Szukis, Sheehan, Alphs, Menges and Lingohr-Smith22,Reference Rizvi, Grima, Tan, Rotzinger, Lin and McIntyre23] and COPD [Reference Rizvi, Grima, Tan, Rotzinger, Lin and McIntyre23,Reference Pilon, Joshi, Sheehan, Zichlin, Zuckerman and Lefebvre26,Reference Sharman Moser, Chodick, Gelerstein, Barit Ben David, Shalev and Stein-Reisner27,Reference Olfson, Amos, Benson, McRae and Marcus30] with not statistical differences in both cases (asthma OR 1.19, 95% CI: 0.00-inf; COPD OR 1.31, 95% CI: 0.01–357,238).

Finally, the mean score in the quality assessment was 6.9 out of 9 points. Twelve of the included studies (80%) received a “Good” quality and the remaining studies (20%) received a “Fair” quality assessment (Supplementary Table 8), with lower results in selection and outcome comparison. The former reflects the tendency for cases to be electronically recorded (ICD codes) instead of medical diagnoses increasing risk of selection bias, while the latter highlights the absence of additional factors or secondary outcomes.

Discussion

This systematic review and meta-analysis of 15 studies, including 476,927 individuals with MDD, is the first to analyze the prevalence and relative risk (measured in OR) of the most frequent respiratory diseases in this population compared to the general population. The COPD likelihood was up to 79% higher in individuals with MDD, even higher in younger individuals and women. Furthermore, the prevalence of asthma in MDD was found to be twice that described in the general population worldwide.

The finding of a significant increase likelihood of COPD, even greater in the younger population, is consistent and of special concer because of the early mortality rates and the reduced life expectancy figures described in individuals with MDD [Reference Lee, Lee, Lee, Park and Kim4]. The finding coincides with that recently published data in other severe mental illnesses such as schizophrenia [Reference Suetani, Honarparvar, Siskind, Hindley, Veronese and Vancampfort7] and bipolar disorder [Reference Laguna-Muñoz, Jiménez-Peinado, Jaén-Moreno, Camacho-Rodríguez, del Pozo and Vieta8], with increased risks of 82 and 73%, respectively, and higher in young people and women with bipolar disorder [Reference Laguna-Muñoz, Jiménez-Peinado, Jaén-Moreno, Camacho-Rodríguez, del Pozo and Vieta8].

The causes of COPD worldwide are well established, with tobacco smoking being a key factor in its development and course [Reference Agustí, Celli, Criner, Halpin, Anzueto and Barnes38]. Individuals with a diagnosis of major depression have higher smoking rates than the general population [Reference Diaz, James, Botts, Maw, Susce and De Leon39] and individuals with mental illness initiate smoking at a younger age, with higher levels of dependence and heavier smoking [Reference Cook, Wayne, Kafali, Liu, Shu and Flores40]. In addition, in a more complex analysis of COPD, factors associated with depression, such as early life adversity, low educational level and low income, unhealthy diets, central obesity, sedentary lifestyles, and sub-chronic levels of inflammation, are linked to lower levels of lung function and, through this, to higher risks and early onset of COPD [Reference Agustí, Vogelmeier and Faner41]. These factors may also explain, together with smoking severity and its early onset, the risk found in younger populations.

COPD in women is a growing public health challenge, with increasing prevalence and mortality at a faster rate than in men [Reference Lugg, Scott, Parekh, Naidu and Thickett42], and it is considered biologically possible that women are more vulnerable to the effect of tobacco smoking and other environmental factors [Reference Polosa and Thomson43]. It is important to highlight the fact that depression is more prevalent in women and that the relationship studied can even be bidirectional or that there is a synergist action, because just as we observed a higher prevalence of COPD in women with MDD, a higher prevalence of depression has been described in women than in men with COPD [Reference Laurin, Lavoie, Bacon, Dupuis, Lacoste and Cartier44]. These findings in women, in the same sense of that described in younger people, translate to an opportunity for the development of preventive strategies especially in these high-risk populations.

Based on more than 250,000 individuals with MDD, the estimated prevalence of asthma (8.6%) doubles the mean described in general population worldwide of 4.3% [Reference Papi, Brightling, Pedersen and Reddel45]. Although the odds of asthma were higher in MDD, the statistical significance was not reached in the OR calculation. The prevalence observed is consistent with two previous meta-analyses describing a possible association, although with less restrictive inclusion criteria [Reference Jiang, Qin and Yang46] and studying whether depression predicts the occurrence of asthma and therefore excluding those studies with depression and asthma at baseline [Reference hua, si, rui, Gao, Shen and chang47]. Figures are also in the line with those recently described by in bipolar disorder [Reference Laguna-Muñoz, Jiménez-Peinado, Jaén-Moreno, Camacho-Rodríguez, del Pozo and Vieta8], with a significant increased risk of asthma. To date, the predominant hypothesis is the possible association of both conditions, which could be mediated through common inflammatory mediators plus the fact that individuals with a mental illness are overexposed to a grater accumulation of health risks.

The adjusted prevalence of these conditions meta-analyzed was close to those described in the general population, being the combined prevalence of a respiratory disease in individuals with MDD of 6.9%. In COPD and adjusted for study location it was 9.0%, with higher prevalence in the USA and European studies (16.3 and 15.5%, respectively) than in Asia (3.0%), which is within the ranges described in the general world population worldwide (8–11%) [Reference Adeloye, Chua, Lee, Basquill, Papana and Theodoratou48,Reference Halbert, Natoli, Gano, Badamgarav, Buist and Mannino49]. The prevalence of pneumonia was 2.5%. There are no comprehensive global epidemiological rates for pneumonia, as these are disaggregated by the etiological pathogen (Staphylococcus, Acinetobacter, Nocardia, COVID, etc.), as evidenced in some studies [Reference Hurley50Reference Rahim, Khan, Shahid, Awan and Irfan55]. When considering the OR and prevalence statistics, it is essential to consider the possibility of underdiagnosis and undertreatment in populations affected by a mental disorder, as highlighted in existing literature – they consult less for medical reasons, they do so in more advanced stages and with higher mortality rates [Reference Cuijpers and Schoevers56]; therefore, there is a greater risk of underestimating differences.

Although early mortality is considered a transdiagnostic issue [Reference Firth, Siddiqi, Koyanagi, Siskind, Rosenbaum and Galletly5] and therefore not limited to severe mental illnesses, these conditions have been associated with the greatest reductions in life expectancy and increased severity in exposure to risk factors [Reference Firth, Siddiqi, Koyanagi, Siskind, Rosenbaum and Galletly57]. Therefore, we examined the subgroup of patients with TRD and found a high adjusted prevalence of respiratory disease (9.9%), even surpassing those reported in bipolar disorder [Reference Laguna-Muñoz, Jiménez-Peinado, Jaén-Moreno, Camacho-Rodríguez, del Pozo and Vieta8]. Our meta-analysis, limited to data on COPD and asthma due to the fewer available studies, did not reveal significant differences in relative risks for the conditions analyzed, compared with MDD.

The results obtained are novel, occur in a highly prevalent mental disorder and are consistent with those previously described in other serious mental disorders. Moreover, they belong to a population with higher rates of early mortality and at risk of not having equal access to preventive healthcare. Nevertheless, this work is not without limitations. First, the analysis has been restricted by the lack of studies in lung cancer, and prevalence figures in TB and pneumonia have been calculated based on only one and two studies, respectively. Second, in COPD, although the heterogeneity parameters found were high, they were significantly reduced by excluding outliers, and the risk figures were maintained (1.81, 95% CI = 1.59–2.06). No publication bias was detected. Third, in the studies reviewed, the evaluation of comorbidities was retrospective and did not control for the respiratory risk variables, such as exposure to perinatal risks, socioeconomic level and general living conditions, cumulative smoking consumption, or exposure to antipsychotic treatment [Reference Ilzarbe and Vieta58]. Fourth, as mentioned earlier, there was not enough statistical power to establish the significance of the numbers found for patients with TRD versus MDD [Reference De Prisco and Vieta59]. Fifth, the absence of comprehensive smoking data across studies to explore and quantify its role as a moderator may have introduced residual confounding, reducing the precision and reliability of the meta-regression results. Last, although 80% of the studies achieved a “good” quality rating, future research should enhance methodology regarding subject selection and the assessment of all comorbidities.

Conclusion

Individuals with MDD show a high prevalence of asthma and an increased risk than the general population of developing COPD, with women and younger people at particular risk. In a common mental disease with higher early mortality rates, equal access to treatment for smoking cessation, detection, and management of other risk factors for respiratory diseases, and early diagnosis and treatment of respiratory diseases should be promoted. The potential for underdiagnosis and undertreatment of respiratory conditions in individuals with MDD underscores the likelihood of underestimation in prevalence estimates. This is a high priority, as underreporting may significantly influence the observed relationship between MDD and the risk of respiratory diseases.

The results found in MDD, and those previously described in schizophrenia and bipolar disorder, should open a debate about the importance of monitoring respiratory function in these populations at risk by means of spirometry, an inexpensive, easy-to-handle, and non-invasive test that is easily implementable.

Supplementary material

The supplementary material for this article can be found at http://doi.org/10.1192/j.eurpsy.2025.13.

Data availability statement

Data are available from the corresponding author upon request.

Acknowledgments

The authors thank María P. Pata for her invaluable support in data analysis.

Author contribution

Study concept and design: F.S., M.J-M., D.L-M., A.J-P. and J.C-V. Acquisition, analysis, or interpretation of data: D.L-M., A.J-P., M.J-M. and C.C-R. Drafting the manuscript: F.S., A.J-P. and D.L-M. Critical revision of the manuscript for important intellectual content: E.V., J.C-V. and F.R-V. Statistical analysis: D.L-M., A.J-P., M.J-M., F.S. and C.C-R. Administrative, technical, or material support: G.I.d.P. and C.C-R. Study supervision: F.S., M.J-M. and J.C-V. A. J-P. and D. L-M. have contributed equally to this work.

Financial support

This study was supported by a grant from the Instituto de Salud Carlos III (PI20/01657) and was co-funded by the European Union.

Competing interest

E.V. reports grants and consulting fees from AB-Biotics, AbbVie, Adamed, Angelini, Biogen, Beckley-Psytech, Biohaven, Boehringer-Ingelheim, Celon Pharma, Compass, Dainippon Sumitomo Pharma, Ethypharm, Ferrer, Gedeon Richter, GHResearch, Glaxo-Smith Kline, HMNC, Idorsia, Johnson & Johnson, Lundbeck, Luye Pharma, Medincell, Merck, Newron, Novartis, Orion Corporation, Organon, Otsuka, Roche, Rovi, Sage, Sanofi-Aventis, Sunovion, Takeda, Teva, and Viatris, outside the submitted work. F.S. during the last 5 years has been speaker for Rovi and Janssen-Cilag. D.L-M. during the last 5 years has been speaker for Lundbeck.

Footnotes

The first two A.J-P. and D.L-M. authors contributed equally to this work.

References

World Health Organization. The global burden of disease: 2004 update. World Health Organization; 2008. 146 p.Google Scholar
Bromet, E, Andrade, LH, Hwang, I, Sampson, NA, Alonso, J, de Girolamo, G, et al. Cross-national epidemiology of DSM-IV major depressive episode. BMC Med. 2011 Dec 26;9(1):90. doi: 10.1186/1741-7015-9-90.Google Scholar
Vos, T, Allen, C, Arora, M, Barber, RM, Bhutta, ZA, Brown, A, et al. Global, regional, and national incidence, prevalence, and years lived with disability for 310 diseases and injuries, 1990–2015: a systematic analysis for the Global Burden of Disease Study 2015. Lancet. 2016 Oct;388(10053):15451602. doi: 10.1016/S0140-6736(16)31678-6.Google Scholar
Lee, SY, Lee, JP, Lee, J, Park, JY, Kim, EY. Association between depressive symptoms and the risk of all-cause and cardiovascular mortality among US adults. Prog Neuropsychopharmacol Biol Psychiatry. 2023 Jul;125:110755. doi: 10.1016/j.pnpbp.2023.110755.Google Scholar
Firth, J, Siddiqi, N, Koyanagi, A, Siskind, D, Rosenbaum, S, Galletly, C, et al. The Lancet Psychiatry Commission: a blueprint for protecting physical health in people with mental illness. Lancet Psychiatry. 2019 Aug;6(8):675712. doi: 10.1016/S2215-0366(19)30132-4.Google Scholar
Fiorillo, A, Sartorius, N. Mortality gap and physical comorbidity of people with severe mental disorders: the public health scandal. Ann Gen Psychiatry. 2021 Dec 13;20(1):52. doi: 10.1186/s12991-021-00374-y.Google Scholar
Suetani, S, Honarparvar, F, Siskind, D, Hindley, G, Veronese, N, Vancampfort, D, et al. Increased rates of respiratory disease in schizophrenia: a systematic review and meta-analysis including 619,214 individuals with schizophrenia and 52,159,551 controls. Schizophr Res. 2021 Nov;237:131140. doi: 10.1016/j.schres.2021.08.022.Google Scholar
Laguna-Muñoz, D, Jiménez-Peinado, A, Jaén-Moreno, MJ, Camacho-Rodríguez, C, del Pozo, GI, Vieta, E, et al. Respiratory disease in people with bipolar disorder: a systematic review and meta-analysis. Mol Psychiatry. 2025 Feb;30(2):777785. doi: 10.1038/s41380-024-02793-1.Google Scholar
Moher, D, Liberati, A, Tetzlaff, J, Altman, DG, Group, PRISMA. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA Statement. Open Med. 2009;3(3):e123e130.Google Scholar
Stroup, DF, Berlin, JA, Morton, SC, Olkin, I, Williamson, GD, Rennie, D, et al. Meta-analysis of observational studies in epidemiology: a proposal for reporting. JAMA. 2000 Apr 19;283(15):20082012. doi: 10.1001/jama.283.15.2008.Google Scholar
American Psychiatric Association. Diagnostic and statistical manual of mental disorders – DSM-IVTR. 4th ed. American Psychiatric Association; 2000.Google Scholar
World Health Organization. The ICD-10 classification of mental and behavioural disorders – diagnostic criteria for research. World Health Organization; 1993.Google Scholar
Global Initiative for Chronic Obstructive Lung Disease. Pocket Guide to COPD diagnosis, management, and prevention – a guide for health care professionals. 2023.Google Scholar
Wells GS, B, O’Connell, D, Peterson, J, Welch, V, Losos, M, Tugwell, P. The Newcastle-Ottawa Scale (NOS) for assessing the quality of nonrandomised studies in meta-analyses [Internet]. Available from: https://www.ohri.ca/programs/clinical_epidemiology/oxford.aspGoogle Scholar
Herzog, R, Álvarez-Pasquin, MJ, Díaz, C, Del Barrio, JL, Estrada, JM, Gil, Á. Are healthcare workers’ intentions to vaccinate related to their knowledge, beliefs and attitudes? A systematic review. BMC Public Health. 2013 Feb 19;13:154.Google Scholar
Higgins, JPT. Measuring inconsistency in meta-analyses. BMJ . 2003 Sep 6;327(7414):557560.Google Scholar
Higgins, JPT, Thompson, SG. Controlling the risk of spurious findings from meta-regression. Stat Med. 2004 Jun 15;23(11):16631682.Google Scholar
R Core Team. R: a language and environment for statistical computing. [Internet]. Vienna, Austria: R Foundation for Statistical Computing; 2021 [cited 2023 Dec 26]. Available from: https://www.R-project.org/.Google Scholar
Viechtbauer, W. Conducting meta-analyses in R with the metafor package. J Stat Softw. 2010;36:148.Google Scholar
Balduzzi, S, Rücker, G, Schwarzer, G. How to perform a meta-analysis with R: a practical tutorial. Evid Based Ment Health. 2019 Nov;22(4):153160.Google Scholar
Harrer, M, Cuijpers, P, Furukawa, TA, Ebert, DD. Doing meta-analysis with R: a hands-on guide [Internet]. 1st ed. Boca Raton, FL and London: Chapman & Hall/CRC Press; 2021.Google Scholar
Lin, J, Szukis, H, Sheehan, JJ, Alphs, L, Menges, B, Lingohr-Smith, M, et al. Economic burden of treatment-resistant Depression among patients hospitalized for major depressive disorder in the United States. Psychiat Res Clin Pract. 2019 Oct 11;1(2):6876. doi: 10.1176/appi.prcp.20190001.Google Scholar
Rizvi, SJ, Grima, E, Tan, M, Rotzinger, S, Lin, P, McIntyre, RS, et al. Treatment-resistant depression in primary care across Canada. Can J Psychiatry. 2014 Jul 1;59(7):349357. doi: 10.1177/070674371405900702.Google Scholar
Ryu, WK, Lee, J, Park, Y, Jung, I, Kang, YA. Incidence and associated risk factors of nontuberculous mycobacterial infection in patients with depression. PLoS One. 2023 Aug 17;18(8):e0290271. doi: 10.1371/journal.pone.0290271.Google Scholar
Schoepf, D, Uppal, H, Potluri, R, Chandran, S, Heun, R. Comorbidity and its relevance on general hospital based mortality in major depressive disorder: a naturalistic 12-year follow-up in general hospital admissions. J Psychiatr Res. 2014;52(1):2835. doi: 10.1016/j.jpsychires.2014.01.010.Google Scholar
Pilon, D, Joshi, K, Sheehan, JJ, Zichlin, ML, Zuckerman, P, Lefebvre, P, et al. Burden of treatment-resistant depression in Medicare: a retrospective claims database analysis. PLoS One. 2019 Oct 10;14(10):e0223255. doi: 10.1371/journal.pone.0223255.Google Scholar
Sharman Moser, S, Chodick, G, Gelerstein, S, Barit Ben David, N, Shalev, V, Stein-Reisner, O. Epidemiology of treatment resistant depression among major depressive disorder patients in Israel. BMC Psychiatry. 2022 Aug 11;22(1):541. doi: 10.1186/s12888-022-04184-8.Google Scholar
DeWaters, AL, Chansard, M, Anzueto, A, Pugh, MJ, Mortensen, EM. The association between major depressive disorder and outcomes in older veterans hospitalized with Pneumonia. Am J Med Sci. 2018;355(1):2126. doi: 10.1016/j.amjms.2017.08.015.Google Scholar
Sweer, L, Martin, DC, Ladd, RA, Miller, JK, Karpf, M. The medical evaluation of elderly patients with major depression. J Gerontol. 1988;43(3):M53M58. doi: 10.1093/geronj/43.3.m53.Google Scholar
Olfson, M, Amos, TB, Benson, C, McRae, J, Marcus, SC. Prospective service use and health care costs of Medicaid beneficiaries with treatment-resistant depression. J Manag Care Spec Pharm. 2018;24(3):226236. doi: 10.18553/jmcp.2018.24.3.226.Google Scholar
Oh, KH, Choi, H, Kim, EJ, Kim, HJ, Cho, SI. Depression & risk of tuberculosis: A nationwide populationbased cohort study. Int J Tuberc Lung Dis. 2017;21(7):804809. doi: 10.5588/ijtld.17.0038.Google Scholar
Shen, TC, Lin, CL, Liao, CH, Wei, CC, Sung, FC, Kao, CH. Major depressive disorder is associated with subsequent adult-onset asthma: a population-based cohort study. Epidemiol Psychiatr Sci. 2017;26(6):664671. doi: 10.1017/S2045796016000664.Google Scholar
Davydow, DS, Ribe, AR, Pedersen, HS, Vestergaard, M, Fenger-Grøn, M. The association of unipolar depression with thirty-day mortality after hospitalization for infection: a population-based cohort study in Denmark. J Psychosom Res. 2016;89:3238. doi: 10.1016/j.jpsychores.2016.08.006.Google Scholar
Chen, C, Chan, HY, Yeh, LL, Pan, YJ. Longitudinal factors associated with mortality in older patients with mood disorders. J Affect Disord. 2021;278. doi: 10.1016/j.jad.2020.09.097.Google Scholar
So-Armah, K, Gupta, SK, Kundu, S, Stewart, JC, Goulet, JL, Butt, AA, et al. Depression and all-cause mortality risk in HIV-infected and HIV-uninfected US veterans: a cohort study. HIV Med. 2019;20(5):317329. doi: 10.1111/hiv.12726.Google Scholar
Balogun, RA, Omotoso, BA, Xin, W, Ma, JZ, Scully, KW, Arogundade, FA, et al. major depression and long-term outcomes of acute kidney injury. Nephron. 2017;135(1):2330. doi: 10.1159/000449474.Google Scholar
Chen, WY, Huang, SJ, Chang, CK, Pan, CH, Su, SS, Yang, TW, et al. Excess mortality and risk factors for mortality among patients with severe mental disorders receiving home care case management. Nord J Psychiatry. 2021;75(2):109117. doi: 10.1080/08039488.2020.1799431.Google Scholar
Agustí, A, Celli, BR, Criner, GJ, Halpin, D, Anzueto, A, Barnes, P, et al. Global initiative for chronic obstructive lung disease 2023 Report: GOLD executive summary. Eur Respir J. 2023 Apr;61(4):2300239. doi: 10.1183/13993003.00239-2023.Google Scholar
Diaz, FJ, James, D, Botts, S, Maw, L, Susce, MT, De Leon, J. Tobacco smoking behaviors in bipolar disorder: a comparison of the general population, schizophrenia, and major depression. Bipolar Disord. 2009 Mar 25;11(2):154165. doi: 10.1111/j.1399-5618.2009.00664.x.Google Scholar
Cook, BL, Wayne, GF, Kafali, EN, Liu, Z, Shu, C, Flores, M. Trends in smoking among adults with mental illness and association between mental health treatment and smoking cessation. JAMA. 2014 Jan 8;311(2):172. doi: 10.1001/jama.2013.284985.Google Scholar
Agustí, A, Vogelmeier, C, Faner, R. COPD 2020: changes and challenges. Am J Physiol Lung Cell Mol Physiol. 2020 Nov 1;319(5):L879L883. doi: 10.1152/ajplung.00429.2020.Google Scholar
Lugg, ST, Scott, A, Parekh, D, Naidu, B, Thickett, DR. Cigarette smoke exposure and alveolar macrophages: mechanisms for lung disease. Thorax. 2022 Jan;77(1):94101. doi: 10.1136/thoraxjnl-2020-216296.Google Scholar
Polosa, R, Thomson, NC. Smoking and asthma: dangerous liaisons. Eur Respir J. 2013 Mar;41(3):716726. doi: 10.1183/09031936.00073312.Google Scholar
Laurin, C, Lavoie, KL, Bacon, SL, Dupuis, G, Lacoste, G, Cartier, A, et al. Sex differences in the prevalence of psychiatric disorders and psychological distress in patients with COPD. Chest. 2007 Jul;132(1):148155. doi: 10.1378/chest.07-0134.Google Scholar
Papi, A, Brightling, C, Pedersen, SE, Reddel, HK. Asthma. Lancet. 2018 Feb;391(10122):783800. doi: 10.1016/S0140-6736(17)33311-1.Google Scholar
Jiang, M, Qin, P, Yang, X. Comorbidity between depression and asthma via immune-inflammatory pathways: a meta-analysis. J Affect Disord. 2014 Sep;166:2229. doi: 10.1016/j.jad.2014.04.027.Google Scholar
hua, Gao Y, si, Zhao H, rui, Zhang F, Gao, Y, Shen, P, chang, Chen R, et al. The Relationship between depression and asthma: a meta-analysis of prospective studies. PLoS One. 2015 Jul 21;10(7):e0132424. doi: 10.1371/journal.pone.0132424.Google Scholar
Adeloye, D, Chua, S, Lee, C, Basquill, C, Papana, A, Theodoratou, E, et al. Global and regional estimates of COPD prevalence: systematic review and meta–analysis. J Glob Health. 2015 Dec;5(2). doi: 10.7189/jogh.05.020415.Google Scholar
Halbert, RJ, Natoli, JL, Gano, A, Badamgarav, E, Buist, AS, Mannino, DM. Global burden of COPD: systematic review and meta-analysis. Eur Respir J. 2006 Sep 1;28(3):523532. doi: 10.1183/09031936.06.00124605.Google Scholar
Hurley, JC. World-wide variation in incidence of Acinetobacter associated ventilator associated pneumonia: a meta-regression. BMC Infect Dis. 2016 Oct 18;16(1):577. doi: 10.1186/s12879-016-1921-4.Google Scholar
Hurley, JC. World-wide variation in incidence of staphylococcus aureus associated ventilator-associated pneumonia: a meta-regression. Microorganisms. 2018 Feb 27;6(1). doi: 10.3390/microorganisms6010018.Google Scholar
Kawamura, K, Ichikado, K, Ichiyasu, H, Anan, K, Yasuda, Y, Suga, M, et al. Acute exacerbation of chronic fibrosing interstitial pneumonia in patients receiving antifibrotic agents: incidence and risk factors from real-world experience. BMC Pulm Med. 2019 Jun 25;19(1):113. doi: 10.1186/s12890-019-0880-0.Google Scholar
Cui, R, Zhu, Y, Wang, Y, Chen, XH, Li, Q, Dai, SM, et al. Tocilizumab in the treatment of coronavirus disease 2019 pneumonia: real-world data from a case series. Future Virol. 2021 May:10.2217/fvl-2020-0410. doi: 10.2217/fvl-2020-0410.Google Scholar
Chen, RY, Li, DW, Wang, JY, Zhuang, SY, Wu, HY, Wu, JJ, et al. Prophylactic effect of low-dose trimethoprim-sulfamethoxazole for Pneumocystis jirovecii pneumonia in adult recipients of kidney transplantation: a real-world data study. Int J Infect Dis. 2022 Dec;125:209215. doi: 10.1016/j.ijid.2022.10.004Google Scholar
Rahim, Y, Khan, J, Shahid, S, Awan, S, Irfan, M. Clinical characteristics, outcomes, and factors associated with mortality in Nocardia pneumonia: 18 years’ real-world data from a tertiary care hospital in Karachi, Pakistan. Respir Investig. 2023 Mar;61(2):254260. doi: 10.1016/j.resinv.2022.11.004.Google Scholar
Cuijpers, P, Schoevers, RA. Increased mortality in depressive disorders: a review. Curr Psychiatry Rep. 2004 Dec;6(6):430437. doi: 10.1007/s11920-004-0007-y.Google Scholar
Firth, J, Siddiqi, N, Koyanagi, A, Siskind, D, Rosenbaum, S, Galletly, C, et al. The Lancet Psychiatry Commission: a blueprint for protecting physical health in people with mental illness. Lancet Psychiatry. 2019 Aug;6(8):675712. doi: 10.1016/S2215-0366(19)30132-4.Google Scholar
Ilzarbe, L, Vieta, E. The elephant in the room: medication as confounder. Eur Neuropsychopharmacol. 2023 Jun;71:68. doi: 10.1016/j.euroneuro.2023.03.001.Google Scholar
De Prisco, M, Vieta, E. The never-ending problem: sample size matters. Eur Neuropsychopharmacol. 2024 Feb;79:1718. doi: 10.1016/j.euroneuro.2023.10.002.Google Scholar
Figure 0

Table 1. Characteristics of included studies

Figure 1

Table 2. Prevalence of respiratory disease in people with major depressive disorder

Figure 2

Figure 1. Forest plot for prevalence of respiratory disease in people with major depressive disorder.

Figure 3

Table 3. Odds Ratio of respiratory disease in people with major depressive disorder compared with controls

Figure 4

Figure 2. Forest plot for Odds Ratio of respiratory disease in people with major depressive disorder compared with controls.

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