Abstract
Importance
Aerobic exercise is an evidence-based treatment for depression. However, current exercise recommendations do not account for the limited functional capacity of patients with chronic illness and comorbid depression. Consequently, these recommendations risk being inappropriate and having low therapeutic application in this population.
Objective
To examine the dose-response relationship between aerobic exercise volume and the severity of depressive symptoms, and to determine the exercise volume needed to alleviate depressive symptoms to the minimally important difference (MID) threshold in patients with chronic illness and comorbid depression.
Data sources
We searched four databases (PubMed, Embase, Web of Science and PsycINFO) for randomised controlled trials published between database inception and May 2025, without language restrictions.
Study selection
We included studies that compared the effects of aerobic exercise interventions with passive controls on depressive symptoms in adults with chronic illness and comorbid depression.
Data extraction and synthesis
Data extraction was performed independently by two reviewers using a standardised form. A random-effects meta-analysis was employed to calculate the pooled estimate (Hedges’ g) and the 95% CI. Meta-regression was conducted to determine the dose-response relationship between aerobic exercise volume and the severity of depressive symptoms.
Main outcome and measure
The prespecified primary outcome was depressive symptoms and was assessed using validated depression rating scales.
Results
36 randomised controlled trials involving 2500 patients were included. Aerobic exercise compared with passive controls reduced the severity of depressive symptoms in patients with chronic illness and comorbid depression (Hedges’ g: −0.73, 95% CI −0.99 to –0.46, p<0.001, I2=81%). Additionally, aerobic exercise had a dose-response effect of −0.01 (95% CI −0.016 to –0.002, p=0.014) per 10 metabolic equivalent of task minutes per week (MET-min/week) on the severity of depressive symptoms. A weekly volume of 405 MET-min/week was found to alleviate depressive symptoms to an extent perceived as important (MID) by patients with chronic illness and comorbid depression.
Conclusions and relevance
This study presents a dose-response relationship between aerobic exercise volume and the severity of depressive symptoms, suggesting that minimal volumes of aerobic exercise can confer improvements. Importantly, it informs stakeholders that achieving the WHO recommendation of 450 MET-min/week is not mandatory to elicit improvements in depressive symptoms. These findings underscore that irrespective of the functional capacity of patients with chronic illness and comorbid depression, aerobic exercise remains a viable strategy to manage their depressive symptoms.
PROSPERO registration number
CRD42021282103.
Keywords: Exercise, Depression, Chronic
WHAT IS ALREADY KNOWN ON THIS TOPIC
Aerobic exercise alleviates depressive symptoms in patients with chronic illness and comorbid depression.
Current exercise recommendations lack consideration for the limited functional capacity of this population and may risk setting unrealistic thresholds to achieve.
WHAT THIS STUDY ADDS
We found a dose-response relationship between weekly aerobic exercise volume (metabolic equivalent of task minutes per week (MET-min/week)) and the severity of depressive symptoms.
HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY
This informs stakeholders that minimal volumes of aerobic exercise can confer improvements and that achieving the WHO’s recommendation of 450 MET-min/week is not mandatory to alleviate depressive symptoms in patients with chronic illness and comorbid depression.
These findings underscore that the prescription of aerobic exercise for depressive symptoms in this population can be person-centred and adjusted according to the functional capacity of the patient.
Introduction
Comorbid depression in patients with chronic illness is an undertreated public health crisis.1 2 Patients with chronic illness have a 1.5-fold to 3.5-fold greater risk of developing depression when compared with healthy individuals.3 4 In patients with cardiac diseases, stroke, diabetes and cancer, comorbid depression exacerbates disease prognosis by increasing the number and severity of complications and by worsening functional capacity. Moreover, comorbid depression significantly compounds their risk of mortality by 1.3-fold to 3-fold relative to their non-depressed counterparts.5,12 Current management guidelines for most chronic illnesses lack specific recommendations for treating comorbid depression.213,15 Consequently, routine treatments for depression, such as pharmacotherapy and psychotherapy, are adopted.13,15 These treatments, however, are limited in patients with chronic illness due to concerns regarding accessibility, costs, drug interactions and adverse events.10 16
A promising treatment for comorbid depression in patients with chronic illness is aerobic exercise.17 However, its current application in patient populations is limited, as exercise recommendations provided by guidelines on depression do not account for their reduced functional capacity.18,21 Indeed, treatment guidelines for depression often align their exercise recommendations with international physical activity guidelines, such as the 450 metabolic equivalent of task minutes per week (MET-min/week) exercise volume (150 min of moderate-intensity (3 METs) aerobic physical activity per week) endorsed by the WHO.22 23 This recommendation, however, may be impractical for patients with chronic illness. For instance, a meta-analysis by Taylor and colleagues on 3990 patients with heart failure found that the functional capacity of these patients was only 65% that of healthy individuals in the same age group.24 Moreover, data from over 400 000 adults in the 2019 Behavioural Risk Factor Surveillance System illustrated that 76% of adults with chronic illness did not meet the WHO recommendation of 450 MET-min/week.25 This underscores the difficulty of implementing and advocating exercise recommendations meant for the general population in patients with chronic illness. Accordingly, given the reduced functional capacity of patients with chronic illness, the need to identify whether minimal volumes of aerobic exercise can alleviate depression in this population is greatly warranted. In addition, identifying an exercise volume that can alleviate depression to a threshold perceived as important by the patients (termed the minimally important difference (MID)) may be of particular value to stakeholders.
To date, no studies have comprehensively investigated the dose-response relationship between aerobic exercise volume and depressive symptoms, and the volume of aerobic exercise necessary to alleviate depression to the MID threshold in patients with chronic illness and comorbid depression. Here, we conducted a systematic review and meta-analysis to determine the effectiveness of aerobic exercise in alleviating depressive symptoms in patients with chronic illness and comorbid depression. Furthermore, we examined the dose-response relationship between aerobic exercise volume and depressive symptoms and established an exercise volume that alleviates depression to the MID threshold in this population.
Methods
This systematic review and meta-analysis adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses reporting guideline (see online supplemental appendix 1),26 and is registered in PROSPERO (CRD42021282103).
Selection criteria
Studies were eligible if they were randomised controlled trials (RCTs) that employed aerobic exercise as the intervention and included participants aged 18 years or older with chronic illness and depression. The study population met eligibility if their chronic illness is listed in the WHO’s 11th revision of the International Classification of Diseases (ICD-11),27 and if their depression is diagnosed by a physician or identified by self-report through meeting clinical cut-offs of validated depression rating scales.
Aerobic exercise was defined according to the American College of Sports Medicine (ACSM) as ‘any activity that uses large muscle groups, can be maintained continuously, and is rhythmic in nature’.28 There were no restrictions concerning the frequency, intensity, session duration and type of aerobic exercise. Studies were excluded if the intervention used other exercise modalities (eg, resistance training), combined aerobic exercise with depression treatments and/or other exercise modalities, or lasted for less than 4 weeks. The comparison group included passive control conditions including usual care, waitlist and patient education.
Outcomes
The primary outcome was the severity of depressive symptoms and was defined as the depression score assessed by validated depression rating scales at follow-up. Studies that measured the severity of depressive symptoms using multiple scales were handled using a hierarchical protocol, whereby the most frequently employed scale was used in the meta-analysis.29 The secondary outcome was drop-out, defined as the number of participants who dropped out of the study before intervention completion.
Information sources and study selection
Four databases (PubMed, Embase, Web of Science and PsycINFO) were searched, without language restriction, for articles published between database inception and 9 May 2025. The search strategy was formulated based on the PICO (Population, Intervention, Comparison, and Outcome) framework (see online supplemental appendix 2). The full texts of all the included studies in three relevant systematic reviews were also assessed.17 30 31 Study selection was performed by two independent reviewers, who screened the title and abstract of all records and full-text reports using Covidence. Conflicts were resolved through discussion or by consensus with a third reviewer when needed. Study investigators were contacted when information pertaining to the eligibility of their study required clarification.
Data extraction
Data extraction was performed independently by two reviewers using a standardised form embedded in an electronic spreadsheet. Summary statistics used to calculate the effect sizes for the primary and secondary outcomes were extracted, including sample sizes, depressive symptoms scores, SD and the number of drop-outs in each study. Intention-to-treat estimates were pooled. Study investigators were contacted when summary statistics were unreported or reported with insufficient detail. If the study investigators did not respond, then the summary statistics, where appropriate, were calculated using methods recommended by Cochrane (see online supplemental appendix 3).32 Trial characteristics (author, year, country and funding status), participant characteristics (age, sex, chronic illness type, baseline severity of depressive symptoms and functional capacity) and comparator and intervention characteristics (control condition type, aerobic exercise type, exercise frequency, intensity, session duration, intervention duration and weekly volume) were also extracted. Chronic illness type was coded according to the ICD-11.27 Functional capacity was coded by benchmarking reference values of age-matched healthy adults.33 34 Intensity of aerobic exercise was coded according to ACSM’s classification of exercise intensity and was coded as categories of intensity (very light, light, moderate and vigorous) and as metabolic equivalents (METs).28 The weekly volume of aerobic exercise was coded as MET-min/week and was determined by multiplying aerobic exercise frequency (times per week) by intensity (METs) and session duration (min). Coding details are provided in online supplemental appendix 4 and 5.
Risk of bias and certainty of evidence assessment
Risk of bias was assessed using Cochrane’s risk-of-bias tool for randomised trials by two independent reviewers.35 Certainty of evidence for the effects of aerobic exercise on alleviating depressive symptoms in patients with chronic illness and comorbid depression was assessed using GRADE (Grading of Recommendations, Assessment, Development and Evaluation).36
Statistical analyses
Statistical analyses were conducted using dmetar and metafor packages in the statistical software R (V.4.4.0) with statistical significance set at p<0.05.37
Hedges’ g was calculated to estimate the effect size between the aerobic exercise intervention and the control condition for depressive symptoms. In line with previous meta-analyses, negative effect sizes denote the superior effects of aerobic exercise interventions on depression when compared with control conditions. To account for the variability in participant, comparator and intervention characteristics and its resulting between-study heterogeneity, a random-effects model using the inverse-variance method and Hartung-Knapp adjustment was employed to estimate the summary Hedges’ g and its 95% CI.37 38 The effect measure for drop-out was adjusted risk ratio (RR) and was estimated using modified Poisson regression with robust sandwich SEs applied to account for within-study clustering.39 The estimation of RR was adjusted for type of illness and age. A forest plot was presented for the meta-analysis and was accompanied by the I2 statistic, which was used to quantify between-study heterogeneity. I2 was interpreted according to Cochrane’s handbook.32
In addition, a meta-regression was performed to explore the dose-response relationship between weekly aerobic exercise volume and the severity of depressive symptoms. To determine the dose-response, the weekly aerobic exercise volume (MET-min/week) was used as the predictor variable. If the weekly volume of the aerobic exercise intervention could not be computed, the study was included in the meta-analysis but excluded from the meta-regression (see online supplemental appendix 5). Furthermore, we determined the weekly volume of aerobic exercise necessary to reduce the severity of depressive symptoms by the MID threshold by adopting the effect size of 0.5 standardised mean difference (SMD) as the threshold. This effect size provides MID estimates that correspond closely to clinical anchor-based MID estimates of validated depression rating scales.40 41
Additional analyses
Sources of heterogeneity were explored by performing moderator analyses for trial, participant, comparator and intervention characteristics. Sensitivity analyses were conducted by excluding studies judged to be outliers, at high risk of bias and by accounting for baseline severity of depressive symptoms. Publication bias was examined by funnel plot and Pustejovsky’s regression,42,44 with p<0.05 indicating funnel plot asymmetry. Subgroups with less than five studies were either combined or excluded from the moderator analyses to reduce false positives and false negatives resulting from multiple comparisons and inadequate power.45
Equity, diversity and inclusion statement
The author group consists of junior, mid-career and senior researchers from both genders, different countries and disciplines. Our study population included both male and female adults with chronic illness and comorbid depression from different demographics, socioeconomics and comorbidities. Our findings may be generalisable to a wide range of individuals.
Results
Search results
We identified 23 481 records from the literature search and screened 15 119 titles and abstracts. This, in combination with the full texts identified from the three systematic reviews,17 30 31 resulted in 269 reports for full-text assessment (figure 1). Overall, 36 unique studies including 2500 patients with chronic illness and comorbid depression met the eligibility criteria. The meta-analysis of the primary outcome included 36 studies (k=37) while the secondary outcome included 30 studies (k=31). A list of the excluded studies and the consensus reason for exclusion is provided in online supplemental appendix 6.
Figure 1. Preferred Reporting Items for Systematic Reviews and Meta-Analyses flow diagram.
Study characteristics
A summary of the characteristics of the included studies is presented in table 1. All 36 studies were RCTs with most studies being funded (n=17) and conducted in Asia (n=11). Study populations mainly had mild-to-moderate severity of depression (n=33) and were comorbid with the following categories of chronic illness: chronic pain (n=8), cardiovascular diseases (n=6), metabolic disorders (n=6), neurological disorders (n=5), cancers (n=3), autoimmune diseases (n=2), respiratory diseases (n=2) and others (n=4) including renal disease, insomnia, anxiety disorder and traumatic brain injury. Although the type of chronic illness varied, a key commonality shared among the studies is the reduced functional capacity of their patients. The median functional capacity relative to age-matched healthy adults is 65% (IQR 51–72) with 74% of the studies reporting a functional capacity of 70% or less in their population when compared with age-matched healthy counterparts. Aerobic exercise interventions were primarily administered as walking or jogging (n=12) or mixed modalities (n=14). Interventions were generally implemented at a moderate intensity (n=20) with the median exercise frequency, session duration and intervention duration being three times per week (IQR 2.5–3), 30 min per session (IQR 30–39) and 12 weeks in length (IQR 8–16).
Table 1. Study characteristics*.
| Study | Funding | Age, mean (SD) | Illness | Severity of depression | Aerobic exercise type | Duration | Sample, n (female) | Measure of depression | Measure of functional capacity | Functional capacity† | ||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Exercise | Control | Exercise | Control | |||||||||
| Abdelbasset 2019 | NR | 52.6 (7.1) 53.4 (6.3) |
52.9 (7.8) | Heart failure | Moderate | Walk, jog | 12 weeks | 23 (7) 23 (5) |
23 (6) | PHQ-9≥5 | VO2max | 45% |
| Abrahão 2016 | NR | 43.8 (14.6) | 46.1 (14.1) | Systemic lupus erythematosus | Moderate | Walk, jog, cycle | 12 weeks | 21 (NR) | 21 (NR) | BDI≥10 | 12MWT | NA |
| Baptista 2012 | NR | 49.5 (NR) | 49.1 (NR) | Fibromyalgia | Moderate | Dance | 16 weeks | 40 (40) | 40 (40) | BDI≥10 | 6MWT | 58% |
| Baquet 2018 | Y | 38.2 (9.6) | 39.6 (9.7) | Multiple sclerosis | Mild | Cycle | 12 weeks | 34 (21) | 34 (25) | QIDS-SR16≥6 | 6MWT | 72% |
| Blumenthal 2012a | Y | 56.7 (10.4) | 55.3 (11.9) | Chronic heart failure | Moderate | Walk, jog, cycle | 12 weeks | 337 (28) | 316 (28) | BDI-II≥14 | 6MWT | 60% |
| Blumenthal 2012b | Y | 64.7 (11.0) | 63.5 (11.4) | Coronary heart disease | Mild | Walk, jog | 16 weeks | 37 (13) | 24 (4) | HAM-D≥8 | VO2max | 65% |
| Boing 2023 | NR | 55.0 (9.9) | 56.8 (11.2) | Breast cancer | Mild | Dance | 16 weeks | 25 (25) | 24 (24) | BDI≥10 | NA | NA |
| Briken 2014 | Y | 49.1 (8.5) 48.8 (6.8) |
50.4 (7.6) | Multiple sclerosis | Mild | Cycle, arm ergometry | 8–10 weeks | 12 (5) 12 (6) |
11 (6) | IDS-SR30≥14 | 6MWT | 50% |
| Davis 2024 | N | 38.6 (8.6) | 34.1 (9.0) | Obesity | Mild | Walk, cycle | 12 weeks | 16 (16) | 17 (17) | PHQ-9≥5 | VO2max | 51% |
| de Groot 2019 | Y | 54.6 (10.7) | 54.2 (10.4) | Type 2 diabetes | Moderate | Walk, jog, cycle | 12 weeks | 34 (26) | 36 (27) | BDI-II≥14 | 6MWT | 67% |
| Eisenhut 2022 | N | 49.1 (13.1) | 53.0 (10.8) | High-grade glioma | Mild | Walk, jog, cycle | 6 weeks | 10 (NR) | 8 (NR) | BDI≥10 | 6MWT | 84% |
| Gary 2010 | Y | NR | NR | Heart failure | Mild | Walk | 12 weeks | 20 (NR) | 17 (NR) | HAM-D≥8 | 6MWT | 59% |
| Gonçalves 2008 | Y | NR | NR | Asthma | Mild | Walk, jog | 12 weeks | 10 (7) | 10 (6) | BDI≥10 | VO2max | 51% |
| Gowans 2001 | Y | 44.6 (8.7) | 49.8 (7.3) | Fibromyalgia | Moderate | Walk, jog | 23 weeks | 27 (24) | 23 (20) | BDI≥10 | 6MWT | 68% |
| Guo 2023 | Y | 20.0 (1.5) | 20.8 (1.8) | Obesity | Mild | HIIT | 4 weeks | 23 (23) | 25 (25) | SDS≥50 | VO2max | 101% |
| Hartescu 2015 | NR | 59.5 (10.6) | 60.1 (8.5) | Insomnia | Mild | Walk | 26 weeks | 20 (15) | 21 (15) | BDI≥10 | NA | NA |
| He 2022 | N | 48.0 (8.6) | 48.3 (10.0) | Breast cancer | Mild | Dance | 16 weeks | 88 (88) | 88 (88) | PHQ-9≥5 | NA | NA |
| Hernando-Garijo 2021 | Y | 51.8 (9.1) | 55.1 (8.5) | Fibromyalgia | Mild | Callisthenics | 15 weeks | 17 (17) | 17 (17) | HADS-D≥8 | 6MWT | 69% |
| Herring 2011 | Y | 20.7 (3.0) | 24.2 (6.3) | Generalised anxiety disorder | Mild | Cycle | 6 weeks | 10 (10) | 10 (10) | BDI-II≥14 | NA | NA |
| Hoffman 2010 | NR | 39.7 (NR) | 37.1 (NR) | Traumatic brain injury | Moderate | Walk, jog, cycle, row | 10 weeks | 42 (NR) | 42 (NR) | BDI≥10 | 6MWT | 65% |
| Kanli 2024 | N | 34.5 (7.0) | 24.8 (6.5) | Chronic low back pain | Moderate | Walk, cycle | 6 weeks | 17 (10) | 17 (6) | BDI≥10 | NA | NA |
| Koukouvou 2004 | NR | 52.3 (9.2) | 52.8 (10.6) | Chronic heart failure | Moderate | Walk, jog, cycle, callisthenics | 26 weeks | 16 (0) | 10 (0) | BDI≥10 | VO2max | 62% |
| Kulcu 2007 | NR | 58.3 (10.5) | 60.4 (11.0) | Congestive heart failure | Moderate | Walk | 8 weeks | 23 (6) | 21 (6) | BDI≥10 | VO2max | 64% |
| Lin 2021 | Y | 62.0 (9.5) | 62.1 (12.3) | End-stage renal disease | Mild | Cycle | 12 weeks | 32 (10) | 32 (13) | BDI≥10 | NA | NA |
| Maharaj 2023 | N | 40.4 (7.2) | 39.9 (5.8) | Type 2 diabetes | Moderate | Walk | 12 weeks | 25 (25) | 24 (24) | BDI-II≥14 | NA | NA |
| Mendes 2010 | Y | NR | NR | Asthma | Mild | NR | 12 weeks | 44 (39) | 45 (35) | BDI≥10 | NA | NA |
| Miyamoto 2019 | NR | 53.4 (8.6) | 51.3 (8.7) | Primary Sjögren’s syndrome | Moderate | Walk | 16 weeks | 23 (23) | 22 (22) | BDI≥10 | VO2max | 66% |
| Negaresh 2019a | NR | 31.2 (3.1) | 29.1 (3.0) | Multiple sclerosis | Moderate | Cycle, arm ergometry | 8 weeks | 17 (11) | 14 (9) | BDI-II≥14 | VO2max | 43% |
| Negaresh 2019b | NR | 32.1 (2.1) | 32.2 (3.3) | Multiple sclerosis and overweight | Moderate | Cycle, arm ergometry | 8 weeks | 17 (11) | 13 (9) | BDI-II≥14 | VO2max | 41% |
| Norouzi 2020 | Y | 35.5 (2.4) 35.5 (2.4) |
35.4 (2.8) | Fibromyalgia | Severe | Walk, jog, dance | 12 weeks | 20 (20) 20 (20) |
20 (20) | BDI-II≥14 | NA | NA |
| Rahimian-Bougar 2022 | N | NR | NR | Chronic joint pain | Moderate | HIIT | 8 weeks | 40 (0) | 40 (0) | DASS-21≥5 | NA | NA |
| Rooks 2007 | Y | 48.0 (11.0) | 51.0 (12.0) | Fibromyalgia | Mild | Walk, jog | 16 weeks | 51 (51) | 50 (50) | BDI≥10 | 6MWT | 78% |
| Sadeghi-Bahmani 2019 | N | 38.0 (8.7) | 37.9 (9.9) | Multiple sclerosis | Moderate | Walk, jog, cycle | 8 weeks | 26 (26) | 21 (21) | BDI-FS≥4 | NA | NA |
| Sañudo 2010 | Y | 55.9 (7.5) | 56.6 (8.7) | Fibromyalgia | Severe | Walk, jog, dance | 24 weeks | 22 (22) | 21 (21) | BDI≥10 | 6MWT | 85% |
| Sarsan 2006 | NR | 41.7 (7.6) | 43.6 (6.5) | Obesity | Mild | Walk, cycle | 12 weeks | 20 (20) | 20 (20) | BDI≥10 | 6MWT | 78% |
| Taheri 2018 | NR | NR | NR | Obesity | Mild | Walk, jog | 8 weeks | 8 (8) | 8 (8) | BDI≥10 | NA | NA |
| Williams 2008 | Y | NR | NR | Alzheimer’s disease | NA | Walk | 16 weeks | 17 (NR) | 12 (NR) | CSDD-19≥7 | NA | NA |
Studies with two or more aerobic exercise interventions were combined to prevent double-counting of participants in the control group.
Functional capacity measured using 6MWT and VO2max was benchmarked to the normative values of age-matched healthy adults reported in Casanova et al and Edvardsen et al.34 35
BDI, Beck Depression Inventory; CSDD, Cornell Scale for Depression in Dementia; DASS, Depression Anxiety and Stress Scale; HADS, Hospital Anxiety and Depression Scale; HAM-D, Hamilton Depression Rating Scale; HIIT, high-intensity interval training; IDS, Inventory of Depressive Symptomatology; 6MWT, 6-minute walk test; 12MWT, 12-minute walk test; N, no; NA, not applicable; NR, not reported; PHQ-9, Patient Health Questionnaire-9; QIDS, Quick Inventory of Depressive Symptomatology; SDS, Zung Self-rating Depression Scale; VO2max, maximal oxygen consumption; Y, yes.
Risk of bias and GRADE
Overall risk of bias was rated as some concerns in 28 studies and high risk in 8 studies, with no studies rated as low risk of bias. The risk of bias rating for individual studies is provided in online supplemental appendix 7. Risk was mostly attributed to the second and fourth domain, which relate to issues of blinding and self-report. Specifically, a primary concern of exercise interventions involving self-report measures is that participants’ awareness of their assigned intervention can influence their assessment of the outcome.46 Therefore, this potential source of bias should be considered when interpreting the results. Based on the GRADE approach, there is low certainty of evidence that the true effect is close to the estimated effect of aerobic exercise on depressive symptoms in patients with chronic illness and comorbid depression (see online supplemental appendix 8). The certainty of evidence was downgraded by two levels due to eight studies being rated as high risk of bias in addition to the high level of heterogeneity in study characteristics.
Effects of aerobic exercise on depressive symptoms and drop-out
Aerobic exercise reduced the severity of depressive symptoms by a large effect size of −0.73 (Hedges’ g) compared with passive controls in adults with chronic illness and comorbid depression (95% CI −0.99 to –0.46, p<0.001, I2=81%, figure 2). Consistent with the main effect, sensitivity analyses excluding studies rated as high risk of bias (Hedges’ g: −0.63, 95% CI −0.89 to –0.38, p<0.001, I2=78), outliers (Hedges’ g: −0.51, 95% CI −0.64 to –0.38, p<0.001, I2=33%) and accounting for baseline severity of depressive symptoms (Hedges’ g: −0.95, 95% CI −1.46 to –0.44, p=0.001, I2=90%) remained statistically significant with moderate to large effect sizes (see online supplemental appendix 9). Publication bias was examined using funnel plot and Pustejovsky’s regression and was not statistically significant (p=0.065, see online supplemental appendix 9 and 10).47 For drop-out, aerobic exercise reported an 18% lower risk when compared with passive controls after accounting for type of illness and age (RR: 0.82, 95% CI 0.69 to 0.98, p=0.028).
Figure 2. Forest plot of the effect of aerobic exercise on the severity of depressive symptoms in adults with chronic illness and comorbid depression. AE, aerobic exercise; CON, control;
Dose-response of aerobic exercise and depressive symptoms
Meta-regression of weekly aerobic exercise volume on the severity of depressive symptoms displayed a dose-response effect of −0.01 (95% CI −0.016 to –0.002, p=0.014, figure 3) per 10 MET-min/week. Sensitivity analyses excluding studies rated as high risk of bias (−0.010, 95% CI −0.018 to –0.002, p=0.015), outliers (−0.005, 95% CI −0.011 to –0.001, p=0.047) and accounting for baseline severity of depressive symptoms (−0.014, 95% CI −0.026 to –0.001, p=0.028) demonstrated consistent findings, illustrating a significant dose-response relationship between weekly aerobic exercise volume and the severity of depressive symptoms (see online supplemental appendix 11-13). Furthermore, a weekly aerobic exercise volume of 405 MET-min/week was found to achieve the MID threshold of 0.5 SMD.
Figure 3. Dose-response effect of weekly aerobic exercise volume on the severity of depressive symptoms in adults with chronic illness and comorbid depression. Meta-regression of weekly aerobic exercise volume on the severity of depressive symptoms displayed a dose-response effect of −0.01 (95% CI −0.016 to –0.002, p=0.014, k=28) per 10 MET-min/week. The shaded area represents the 95% confidence band. The plotted points correspond to the individual studies with the point size representing the study’s weight in the meta-regression. The red line corresponds to 0.5 SMD and represents the MID threshold. MET-min/week, metabolic equivalent of task minutes per week; MID, minimally important difference; SMD, standardised mean difference.
Moderator analyses
The results of the moderator analyses are presented in online supplemental appendix 14. Briefly, none of the chosen moderators for meta-regression (other than weekly aerobic exercise volume) exhibited a dose-response effect. Subgroup analyses for funding status, severity of baseline depression, type of control, type of aerobic exercise, exercise frequency, intensity and session duration did not present significant between-group differences and were comparable in effect sizes. However, the subgroup analysis of chronic illness type did reveal that populations with neurological disorders had lower effect sizes.
Discussion
This meta-analysis supports the effectiveness of aerobic exercise for alleviating depressive symptoms and extends previous reviews by presenting a novel dose-response relationship between weekly aerobic exercise volume and the severity of depressive symptoms in adults with chronic illness and comorbid depression. The identification of this dose-response relationship informs guidelines, healthcare professionals and stakeholders that even minimal volumes of aerobic exercise can alleviate depressive symptoms in this population. This finding holds particular significance to patients with chronic illness and comorbid depression, who are often burdened by a reduced functional capacity, as it underscores aerobic exercise as a viable therapeutic strategy to manage their depressive symptoms. This study further identified that achieving a weekly aerobic exercise volume of 405 MET-min/week can reduce depressive symptoms to an extent that is of perceivable importance (MID) to the population.
Existing treatment guidelines for depression lack evidence-based exercise recommendations tailored to adults with chronic illness and comorbid depression.13 14 48 Consequently, guidelines commonly adopt physical activity recommendations meant for the general population, such as the WHO recommendation of at least 450 MET-min/week of aerobic physical activity.22 23 While this recommendation may be achievable for adults who are depressed but otherwise healthy, for those who have chronic illness and comorbid depression this recommendation may pose a significant barrier given that their chronic conditions result in substantial physical and functional impairments, which limit their functional capacity.11 Moreover, as comorbid depression worsens fatigue and motivation, this can magnify the difficulty of achieving this recommendation in patients with chronic illness. Accordingly, advocating and implementing exercise recommendations meant for the general population in this population may be inappropriate and risk setting an unrealistic threshold. Thus, potentially discouraging these patients from engaging in any aerobic exercise activity. In this study, 74% of the studies reported a functional capacity of 70% or less compared with age-matched healthy counterparts. This observation is consistent with the literature. For example, patients with heart failure were shown to walk 363 m in the 6-minute walk test whereas healthy adults in the same age group walked 559 m.24 Similarly, adults with multiple sclerosis performed significantly fewer daily steps (5840 steps per day) compared with age-matched healthy counterparts (9685 steps per day).49 Compounding this reduced functional capacity in patients with chronic illness, comorbid depression is further associated with greater disability. Indeed, 46% of adults with chronic illness and comorbid depression experience moderate-to-severe disability compared with 17% in those with chronic illness only.50 Collectively, these considerations underscore the need to determine whether minimal volumes of aerobic exercise can alleviate depressive symptoms in this population.
This study presents a dose-response relationship between weekly aerobic exercise volume and the severity of depressive symptoms, suggesting that even minimal volumes of aerobic exercise can confer improvements. This frames aerobic exercise as a viable strategy for depressive symptoms in patients with chronic illness regardless of their functional capacity. Additionally, it informs stakeholders that adhering to the WHO’s weekly aerobic exercise target of 450 MET-min/week is not required to see improvements in depressive symptoms. This may lower perceived barriers to exercise adoption in patients with chronic illness. Furthermore, this study found that a weekly volume of 405 MET-min/week can reduce depressive symptoms to an extent that is of perceivable importance (MID) to the patients. Therefore, patients with chronic illness and comorbid depression, if given the functional capacity, time and willingness, may consider exercising at this weekly volume to potentially observe a reduction in depressive symptoms that is meaningful. Of note, the reference exercise volume of 405 MET-min/week aligns closely with the WHO recommendation of 450 MET-min/week. As the median functional capacity was 65% in this study, we acknowledge that it is unlikely that patients with chronic illness will readily achieve the reference exercise volume. Thus, most patients with chronic illness will need to start small and gradually progress to this reference exercise volume. Encouragingly, the dose-response relationship supports that any volume of exercise is beneficial, as such a stepwise approach to achieving the reference exercise volume via incremental increases is appropriate.
This meta-analysis corroborates previous reviews but advances the field in two key aspects.30 31 First, this study is the first to demonstrate a dose-response relationship between weekly aerobic exercise volume and the severity of depressive symptoms in patients with chronic illness, supplemented by a weekly volume to achieve an MID reduction in depressive symptoms. Second, this study reports a larger effect size for aerobic exercise than previous reviews. This is likely due to the exclusion of studies that did not meet the threshold for mild depression, whereas previous reviews included studies with baseline depression scores in the normal range. Several limitations warrant consideration. First, there was considerable heterogeneity across study populations, as the type of chronic illness varied. This reduced the specificity of the results. However, this heterogeneity is also a strength as it increases the generalisability of the findings. Moreover, given the importance of identifying a dose-response in this population, we chose to employ an inclusive approach. Future research should validate whether the observed linear pattern persists or shifts towards a curvilinear trajectory as additional studies accumulate, especially within specific chronic illness types. Second, methodological limitations necessitate cautious interpretation of the findings. The between-study effect size distribution for the primary outcome exhibited skewness and may have affected the pooled estimates.51 Although the sensitivity analysis excluding outliers presented a normal distribution and corroborated the main findings. There is also a possibility of small-sample bias as four included studies had a sample size of ≤10 per group.52 Additionally, the estimation of RR may be influenced by sparse-data bias due to the low cases of drop-out across all included studies.53 Third, moderator analyses were exploratory and likely to be underpowered. Thus, its findings and application should also be interpreted with caution. Fourth, most studies did not report adverse events; this prevented definitive conclusions about the safety of aerobic exercise as a treatment strategy for depression. Indeed, while the adjusted RR for dropout in the aerobic exercise is 0.82 (95% CI 0.69 to 0.98), this estimate should be interpreted cautiously as the CI is wide.
Overall, our findings suggest that performing any volume of aerobic exercise is beneficial for reducing depressive symptoms in patients with chronic illness and comorbid depression. Specifically, performing aerobic exercise at 405 MET-min/week can lead to reductions in depressive symptoms that are of perceivable importance to the patients themselves. These findings offer exercise recommendations that are applicable to patients with chronic illness and comorbid depression, and indicate that the prescription of aerobic exercise for depressive symptoms in this population can be person-centred and adjusted according to the functional capacity of the patient.
Supplementary material
Acknowledgements
We thank all contacted authors for providing data for this study.
Footnotes
Funding: This study was supported by the Research Impact Fund (R7024-20) and General Research Funds (17110722 and 17112223) of Research Grants Council of the Hong Kong University Grants Committee, Health and Medical Research Fund (17182461) of the Health Bureau, Hong Kong Special Administrative Region Government, and the Seed Fund for Basic Research and the HKU Presidential PhD Scholar Programme of The University of Hong Kong.
Provenance and peer review: Not commissioned; externally peer reviewed.
Patient consent for publication: Not applicable.
Ethics approval: Not applicable.
Data availability statement
Data are available upon reasonable request.
References
- 1.Moussavi S, Chatterji S, Verdes E, et al. Depression, chronic diseases, and decrements in health: results from the World Health Surveys. Lancet. 2007;370:851–8. doi: 10.1016/S0140-6736(07)61415-9. [DOI] [PubMed] [Google Scholar]
- 2.Gold SM, Köhler-Forsberg O, Moss-Morris R, et al. Comorbid depression in medical diseases. Nat Rev Dis Primers. 2020;6:69. doi: 10.1038/s41572-020-0200-2. [DOI] [PubMed] [Google Scholar]
- 3.Polsky D, Doshi JA, Marcus S, et al. Long-term risk for depressive symptoms after a medical diagnosis. Arch Intern Med. 2005;165:1260–6. doi: 10.1001/archinte.165.11.1260. [DOI] [PubMed] [Google Scholar]
- 4.Chang-Quan H, Xue-Mei Z, Bi-Rong D, et al. Health status and risk for depression among the elderly: a meta-analysis of published literature. Age Ageing. 2010;39:23–30. doi: 10.1093/ageing/afp187. [DOI] [PubMed] [Google Scholar]
- 5.Penninx BW, Beekman AT, Honig A, et al. Depression and cardiac mortality: results from a community-based longitudinal study. Arch Gen Psychiatry. 2001;58:221–7. doi: 10.1001/archpsyc.58.3.221. [DOI] [PubMed] [Google Scholar]
- 6.Blumenthal JA, Lett HS, Babyak MA, et al. Depression as a risk factor for mortality after coronary artery bypass surgery. Lancet. 2003;362:604–9. doi: 10.1016/S0140-6736(03)14190-6. [DOI] [PubMed] [Google Scholar]
- 7.Cai W, Mueller C, Li Y-J, et al. Post stroke depression and risk of stroke recurrence and mortality: A systematic review and meta-analysis. Ageing Res Rev. 2019;50:102–9. doi: 10.1016/j.arr.2019.01.013. [DOI] [PubMed] [Google Scholar]
- 8.Prigge R, Wild SH, Jackson CA. Depression, diabetes, comorbid depression and diabetes and risk of all-cause and cause-specific mortality: a prospective cohort study. Diabetologia. 2022;65:1450–60. doi: 10.1007/s00125-022-05723-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Wang X, Wang N, Zhong L, et al. Prognostic value of depression and anxiety on breast cancer recurrence and mortality: a systematic review and meta-analysis of 282,203 patients. Mol Psychiatry. 2020;25:3186–97. doi: 10.1038/s41380-020-00865-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Berk M, Köhler‐Forsberg O, Turner M, et al. Comorbidity between major depressive disorder and physical diseases: a comprehensive review of epidemiology, mechanisms and management. World Psychiatry. 2023;22:366–87. doi: 10.1002/wps.21110. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Stein MB, Cox BJ, Afifi TO, et al. Does co-morbid depressive illness magnify the impact of chronic physical illness? A population-based perspective. Psychol Med. 2006;36:587–96. doi: 10.1017/S0033291706007239. [DOI] [PubMed] [Google Scholar]
- 12.Katon WJ. Epidemiology and treatment of depression in patients with chronic medical illness. Dialogues Clin Neurosci. 2011;13:7–23. doi: 10.31887/DCNS.2011.13.1/wkaton. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Vaccarino V, Badimon L, Bremner JD, et al. Depression and coronary heart disease: 2018 position paper of the ESC working group on coronary pathophysiology and microcirculation. Eur Heart J. 2020;41:1687–96. doi: 10.1093/eurheartj/ehy913. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Young-Hyman D, de Groot M, Hill-Briggs F, et al. Psychosocial Care for People With Diabetes: A Position Statement of the American Diabetes Association. Diabetes Care. 2016;39:2126–40. doi: 10.2337/dc16-2053. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Grassi L, Caruso R, Riba MB, et al. Anxiety and depression in adult cancer patients: ESMO Clinical Practice Guideline. ESMO Open. 2023;8:101155. doi: 10.1016/j.esmoop.2023.101155. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Zimmermann-Viehoff F, Kuehl LK, Danker-Hopfe H, et al. Antidepressants, autonomic function and mortality in patients with coronary heart disease: data from the Heart and Soul Study. Psychol Med. 2014;44:2975–84. doi: 10.1017/S003329171400066X. [DOI] [PubMed] [Google Scholar]
- 17.Noetel M, Sanders T, Gallardo-Gómez D, et al. Effect of exercise for depression: systematic review and network meta-analysis of randomised controlled trials. BMJ. 2024;384:e075847. doi: 10.1136/bmj-2023-075847. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Stubbs B, Vancampfort D, Hallgren M, et al. EPA guidance on physical activity as a treatment for severe mental illness: a meta-review of the evidence and Position Statement from the European Psychiatric Association (EPA), supported by the International Organization of Physical Therapists in Mental Health (IOPTMH) Eur Psychiatry. 2018;54:124–44. doi: 10.1016/j.eurpsy.2018.07.004. [DOI] [PubMed] [Google Scholar]
- 19.Lam RW, Kennedy SH, Parikh SV, et al. Canadian Network for Mood and Anxiety Treatments (CANMAT) 2016 Clinical Guidelines for the Management of Adults with Major Depressive Disorder: Introduction and Methods. Can J Psychiatry . 2016;61:506–9. doi: 10.1177/0706743716659061. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Malhi GS, Bell E, Bassett D, et al. The 2020 Royal Australian and New Zealand College of Psychiatrists clinical practice guidelines for mood disorders. Aust N Z J Psychiatry. 2021;55:7–117. doi: 10.1177/0004867420979353. [DOI] [PubMed] [Google Scholar]
- 21.National Institute for Health and Care Excellence . NICE; 2022. Depression in adults: treatment and management. [PubMed] [Google Scholar]
- 22.World Health Organization . Geneva: World Health Organization; 2020. WHO guidelines on physical activity and sedentary behavior. [Google Scholar]
- 23.Bull FC, Al-Ansari SS, Biddle S, et al. World Health Organization 2020 guidelines on physical activity and sedentary behaviour. Br J Sports Med. 2020;54:1451–62. doi: 10.1136/bjsports-2020-102955. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Taylor RS, Walker S, Smart NA, et al. Impact of Exercise Rehabilitation on Exercise Capacity and Quality-of-Life in Heart Failure: Individual Participant Meta-Analysis. J Am Coll Cardiol. 2019;73:1430–43. doi: 10.1016/j.jacc.2018.12.072. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Alqahtani SM, Pavela G, Pekmezi D, et al. Are US Adults With Chronic Health Conditions Meeting Public Health Recommendations for Physical Activity? JOSPT Open. 2024;2:115–24. doi: 10.2519/josptopen.2024.1130. [DOI] [Google Scholar]
- 26.Page MJ, McKenzie JE, Bossuyt PM, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ. 2021;372:n71. doi: 10.1136/bmj.n71. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.World health organization . Geneva: World Health Organization; International classification of diseases, eleventh revision (ICD-11) [Google Scholar]
- 28.American College of Sports Medicine . ACSM’s guidelines for exercise testing and prescription. 11th. Wolters Kluwer; 2022. edn. [DOI] [PubMed] [Google Scholar]
- 29.Recchia F, Leung CK, Chin EC, et al. Comparative effectiveness of exercise, antidepressants and their combination in treating non-severe depression: a systematic review and network meta-analysis of randomised controlled trials. Br J Sports Med. 2022;56:1375–80. doi: 10.1136/bjsports-2022-105964. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Béland M, Lavoie KL, Briand S, et al. Aerobic exercise alleviates depressive symptoms in patients with a major non-communicable chronic disease: a systematic review and meta-analysis. Br J Sports Med. 2020;54:272–8. doi: 10.1136/bjsports-2018-099360. [DOI] [PubMed] [Google Scholar]
- 31.Herring MP, Puetz TW, O’Connor PJ, et al. Effect of exercise training on depressive symptoms among patients with a chronic illness: a systematic review and meta-analysis of randomized controlled trials. Arch Intern Med. 2012;172:101–11. doi: 10.1001/archinternmed.2011.696. [DOI] [PubMed] [Google Scholar]
- 32.Higgins JPT, Thomas J, Chandler J, et al. Cochrane handbook for systematic reviews of interventions version 6.4. Cochrane; 2023. [Google Scholar]
- 33.Casanova C, Celli BR, Barria P, et al. The 6-min walk distance in healthy subjects: reference standards from seven countries. Eur Respir J. 2011;37:150–6. doi: 10.1183/09031936.00194909. [DOI] [PubMed] [Google Scholar]
- 34.Edvardsen E, Hansen BH, Holme IM, et al. Reference values for cardiorespiratory response and fitness on the treadmill in a 20- to 85-year-old population. Chest. 2013;144:241–8. doi: 10.1378/chest.12-1458. [DOI] [PubMed] [Google Scholar]
- 35.Sterne JAC, Savović J, Page MJ, et al. RoB 2: a revised tool for assessing risk of bias in randomised trials. BMJ. 2019;366:l4898. doi: 10.1136/bmj.l4898. [DOI] [PubMed] [Google Scholar]
- 36.Schünemann H, Brożek J, Guyatt G, editors. Handbook for grading the quality of evidence and the strength of recommendations using the grade approach. 2013. https://guidelinedevelopment.org/handbook Available.
- 37.Harrer M, Cuijpers P, Furukawa TA, et al. Doing meta-analysis with R: a hands-on guide. Boca Raton, FL and London: Chapmann & Hall/CRC Press; 2021. [Google Scholar]
- 38.Knapp G, Hartung J. Improved tests for a random effects meta-regression with a single covariate. Stat Med. 2003;22:2693–710. doi: 10.1002/sim.1482. [DOI] [PubMed] [Google Scholar]
- 39.Zou G. A modified poisson regression approach to prospective studies with binary data. Am J Epidemiol. 2004;159:702–6. doi: 10.1093/aje/kwh090. [DOI] [PubMed] [Google Scholar]
- 40.Angst F, Aeschlimann A, Angst J. The minimal clinically important difference raised the significance of outcome effects above the statistical level, with methodological implications for future studies. J Clin Epidemiol. 2017;82:128–36. doi: 10.1016/j.jclinepi.2016.11.016. [DOI] [PubMed] [Google Scholar]
- 41.Hengartner MP, Plöderl M. Estimates of the minimal important difference to evaluate the clinical significance of antidepressants in the acute treatment of moderate-to-severe depression. BMJ Evid Based Med. 2022;27:69–73. doi: 10.1136/bmjebm-2020-111600. [DOI] [PubMed] [Google Scholar]
- 42.Egger M, Davey Smith G, Schneider M, et al. Bias in meta-analysis detected by a simple, graphical test. BMJ. 1997;315:629–34. doi: 10.1136/bmj.315.7109.629. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 43.Pustejovsky JE, Rodgers MA. Testing for funnel plot asymmetry of standardized mean differences. Res Synth Methods. 2019;10:57–71. doi: 10.1002/jrsm.1332. [DOI] [PubMed] [Google Scholar]
- 44.Duval S, Tweedie R. Trim and fill: A simple funnel-plot-based method of testing and adjusting for publication bias in meta-analysis. Biometrics. 2000;56:455–63. doi: 10.1111/j.0006-341x.2000.00455.x. [DOI] [PubMed] [Google Scholar]
- 45.Burke JF, Sussman JB, Kent DM, et al. Three simple rules to ensure reasonably credible subgroup analyses. BMJ. 2015;351:h5651. doi: 10.1136/bmj.h5651. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 46.Boutron I, Altman DG, Moher D, et al. CONSORT Statement for Randomized Trials of Nonpharmacologic Treatments: A 2017 Update and a CONSORT Extension for Nonpharmacologic Trial Abstracts. Ann Intern Med. 2017;167:40–7. doi: 10.7326/M17-0046. [DOI] [PubMed] [Google Scholar]
- 47.Peters JL, Sutton AJ, Jones DR, et al. Performance of the trim and fill method in the presence of publication bias and between-study heterogeneity. Stat Med. 2007;26:4544–62. doi: 10.1002/sim.2889. [DOI] [PubMed] [Google Scholar]
- 48.Colberg SR, Sigal RJ, Yardley JE, et al. Physical Activity/Exercise and Diabetes: A Position Statement of the American Diabetes Association. Diabetes Care. 2016;39:2065–79. doi: 10.2337/dc16-1728. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 49.Casey B, Coote S, Galvin R, et al. Objective physical activity levels in people with multiple sclerosis: Meta-analysis. Scand J Med Sci Sports. 2018;28:1960–9. doi: 10.1111/sms.13214. [DOI] [PubMed] [Google Scholar]
- 50.Deschênes SS, Burns RJ, Schmitz N. Associations between depression, chronic physical health conditions, and disability in a community sample: A focus on the persistence of depression. J Affect Disord. 2015;179:6–13. doi: 10.1016/j.jad.2015.03.020. [DOI] [PubMed] [Google Scholar]
- 51.Rubio-Aparicio M, López-López JA, Sánchez-Meca J, et al. Estimation of an overall standardized mean difference in random-effects meta-analysis if the distribution of random effects departs from normal. Res Synth Methods. 2018;9:489–503. doi: 10.1002/jrsm.1312. [DOI] [PubMed] [Google Scholar]
- 52.Lin L. Bias caused by sampling error in meta-analysis with small sample sizes. PLoS One. 2018;13:e0204056. doi: 10.1371/journal.pone.0204056. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 53.Greenland S, Mansournia MA, Altman DG. Sparse data bias: a problem hiding in plain sight. BMJ. 2016;352:i1981. doi: 10.1136/bmj.i1981. [DOI] [PubMed] [Google Scholar]
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Supplementary Materials
Data Availability Statement
Data are available upon reasonable request.



