Chronic lung diseases (CLDs), especially chronic obstructive pulmonary disease (COPD), are significant contributors to the rising global morbidity and mortality rates (GBD 2021 Diseases and Injuries Collaborators, 2024; GBD Chronic Respiratory Disease Collaborators, 2020; GBD 2019 Chronic Respiratory Diseases Collaborators, 2023; Adeloye et al., 2022; Al Wachami et al., 2024). With the aging of populations and increasing environmental pollution, COPD has become the third leading cause of death worldwide (GBD 2021 Diseases and Injuries Collaborators, 2024; GBD Chronic Respiratory Disease Collaborators, 2020; GBD 2019 Chronic Respiratory Diseases Collaborators, 2023; Adeloye et al., 2022; Al Wachami et al., 2024). CLDs not only impair respiratory function and quality of life but are also frequently accompanied by multiple comorbidities, with depressive symptoms being particularly common and severe (Zhang et al., 2011; Zheng et al., 2022; Yohannes and Alexopoulos, 2014). These comorbid conditions exacerbate the overall disease burden and contribute to heightened hospitalization rates, prolonged hospital stays, escalated healthcare costs, and increased mortality (Zhang et al., 2011; Zheng et al., 2022; Yohannes and Alexopoulos, 2014). Despite the well-recognized high prevalence of depressive symptoms among patients with CLDs, the contributing factors and underlying mechanisms remain insufficiently studied. Current research has focused on factors such as disease severity (Kim et al., 2014), respiratory difficulties (Bestall et al., 1999), diminished quality of life (Pedrozo-Pupo et al., 2021), and insufficient social support (Stoustrup et al., 2024). However, there is a relative paucity of research examining the relationships between potentially modifiable factors, such as grip strength (GS), sleep quality, and comorbidities, and depressive symptoms. This gap underscores the need for further investigation into these potentially alterable influences to better understand and manage depression in the context of CLDs.

GS, as a simple, quick, and cost-effective measure, is widely recognized as a reliable indicator for overall muscle strength (Norman et al., 2011). In recent years, the association between GS and various health outcomes has garnered significant attention from researchers. Evidence suggests associations between GS and cognitive function, physical performance, and metabolic health, indicating that GS may reflect not only physical but also mental resilience (Muhammad and Maurya, 2022). Additionally, lower GS has been linked to inflammatory processes, which are known contributors to depression (Granic et al., 2017). Given the prevalent decline in muscle function and overall physical capacity among patients with CLDs, an investigation into the relationship between GS and depressive symptoms could offer a novel perspective. This approach may facilitate the early detection and proactive management of high-risk individuals.

Lifestyle factors, including smoking, alcohol consumption, physical activity intensity, and sleep quality, have been demonstrated to correlate with mental health in the general population (Zhong et al., 2019). Notably, sleep disorders, in particular, are a common complication among patients with CLDs (Du et al., 2023) and a significant factor affecting quality of life. The influence of sleep duration on the development and exacerbation of depressive symptoms in patients with CLDs, however, remains uncharacterized. Given the propensity for respiratory difficulties in patients with CLDs to compromise sleep quality, a focused study on the impacts of sleep duration on their mental health holds considerable clinical relevance. Moreover, patients with CLDs frequently suffer from various comorbidities, such as cardiovascular diseases, diabetes, and osteoporosis (Cavaillès et al., 2013). These comorbid conditions not only complicate medical management but may also have profound implications for their mental health (Negewo et al., 2015). Despite its importance, research exploring the link between comorbidities and depressive symptoms in patients with CLDs remains limited. Understanding the impact of comorbidities on depression risk is essential for developing comprehensive management strategies and improving patient outcomes.

In recent years, network analysis methods have witnessed widespread application in psychiatric and psychological research (Borsboom and Cramer, 2013; Borsboom, 2017; Zhong et al., 2023). This approach can dissect the complex interactions between symptoms beyond the reach of conventional statistical techniques. Despite their potential, network analysis methods have been scarcely applied in the study of depressive symptoms among patients with CLDs. This emerging method, which explores the complex network of relationships between depressive symptoms, GS, sleep duration, and comorbidities, may provide new insights into the mechanisms of depression development and the formulation of targeted intervention strategies.

Given the current research landscape, this study aimed to address existing gaps by thoroughly exploring the associations of GS, sleep duration, and comorbidities with depressive symptoms in patients with CLDs utilizing data from the China Health and Retirement Longitudinal Study (CHARLS) (Zhang et al., 2023; Zhao et al., 2014). The specific objectives of this study are to evaluate the prevalence of depressive symptoms among patients with CLDs and their relationships with demographic characteristics, to investigate the associations of GS, sleep duration, and comorbidities with depressive symptoms, and to identify variations in these associations across different subpopulations through subgroup analyses. Additionally, the study intended to examine the complex network relationships between these factors and specific depressive symptoms using heatmaps and network analysis methods. The insights gained from this study may enhance the understanding of the influencing factors and underlying mechanisms of depressive symptoms in patients with CLDs. This study could potentially inform the development of targeted prevention and intervention strategies, thereby contributing to improvements in the mental health and quality of life of this vulnerable population.

This study, based on data from the CHARLS, utilized binary regression analysis, subgroup analysis, correlation analysis, and network analysis to comprehensively investigate the associations and underlying mechanisms of GS, sleep duration, and CCDs with depressive symptoms in patients with CLDs. The findings illuminated complex relational networks between these factors and depressive symptoms, offering new perspectives for understanding and intervening in depressive symptoms among patients with CLDs. The 39.8% prevalence of depressive symptoms underscores the severity of depression in patients with CLDs and highlights the critical need for mental health support within this group.

Our findings confirmed a significant negative correlation between GS and depressive symptoms, corroborating previous research findings. For instance, Gu et al. (2021) uncovered that lower GS was associated with a higher risk of depression in a large-scale cohort study of the general adult population in China. Our research extends this finding to patients with CLDs, and highlights that this association is particularly pronounced in various subgroups such as both men and women and different age groups. The correlation was also significant regardless of social activity participation, indicating its broad relevance in the context of CLDs. These observations propose that GS could serve as a straightforward and effective indicator for assessing and preventing depressive symptoms in patients with CLDs. Reduced GS, indicative of overall muscle strength, may reflect a decline in physical function in patients with CLDs, which may adversely affect their mental health (Sepúlveda-Loyola et al., 2020). The deterioration of physical function is often accompanied by limited physical activity, which in turn increases social isolation and feelings of helplessness, all of which are known risk factors for depression. Additionally, the decline in muscle strength in patients with chronic lung disease may be associated with chronic low-grade inflammation, which is considered an important biological mechanism of depression (Heresco-Levy et al., 2024). At the same time, fatigue is a common symptom in patients with chronic lung disease, and low grip strength may be associated with increased fatigue. Fatigue restricts participation in daily activities, leading individuals to feel unable to cope with everyday challenges, thus increasing the risk of depression. Furthermore, our research validated the negative correlation between sleep duration and depressive symptoms (Gebara et al., 2018; Fang et al., 2019). This relationship was more prominent in subgroups of younger individuals, underweight individuals, current drinkers, and those engaged in moderate physical activities. These findings highlight the critical role of sleep quality improvement in both the preventive and therapeutic management of depressive symptoms among patients with CLDs. Sleep disorders may exacerbate depressive symptoms in patients with CLDs by affecting the neuroendocrine system and immune function. Importantly, our study underscores the relevance of sleep duration as a quantifiable measure and a practical intervention target for clinical settings. Additionally, a positive correlation exists between the number of CCDs and depressive symptoms, with this association being more significant among older males, never drinkers, and those with low physical activity intensity. This finding suggests that the coexistence of multiple chronic conditions may augment the psychological burden on patients with CLDs, thereby increasing their susceptibility to depression. These findings are consistent with prior meta-analyses, which highlighted the detrimental impact of COPD coexisting with multiple chronic diseases on mental health. Our study further quantified this relationship and identified specific high-risk subgroups, offering enhanced precision in guiding clinical practice to mitigate these risks.

The network analysis results further unveiled the complex relationships between depressive symptoms and factors such as GS, sleep duration, and CCDs. The symptom “depressed,” serving as a core symptom, is extensively connected with other symptoms and factors, indicating its potential role as a key node driving the entire symptom network. Moreover, the robust associations between various factors and specific depressive symptoms (such as GS with “exhausted” and “unhappy,” and sleep duration with “lonely”) suggest potential directions for targeted interventions. These observations are consistent with the depressive symptom network theory proposed by Fried et al. (2016), which underscores the critical need to comprehend the interactions among symptoms. Our study extended this theoretical framework to patients with CLDs and provided more detailed and specific insights into depression in this specific patient population.

These findings carry important implications for clinical management and public health strategies in patients with CLDs. The assessment of GS emerges as a crucial aspect. As a straightforward, rapid, and cost-effective diagnostic measure, GS can be incorporated into the routine assessments of patients with CLDs. Its utility extends beyond evaluating physical function and also acts as a predictive indicator for depression risk. Consequently, clinicians are advised to consider enhanced psychological health surveillance and proactive interventions for individuals exhibiting diminished GS. This recommendation resonates with the suggestions provided by Celis-Morales et al. (2018), who also underscored the value of the incorporation of GS evaluations into routine health assessments. The study also highlights the pivotal role of sleep management in maintaining the mental health of patients with CLDs. Healthcare providers are advised to intensify their focus on sleep disturbances, facilitate education on sleep hygiene, and implement behavioral or pharmacological treatments as needed to improve sleep quality in this specific patient population. Enhanced sleep management is particularly crucial for younger patients, underweight individuals, and individuals who regularly consume alcohol, as they may experience more significant mental health benefits from improved sleep management. Correspondingly, this finding aligns with the research conducted by Omachi et al. (2012), which highlighted the importance of improving sleep quality in patients with COPD. Moreover, integrated management for patients with CLDs and multiple chronic conditions is another essential aspect highlighted by the study. An integrated management strategy should include the coordination of multidisciplinary teams to develop holistic treatment plans that cater to both the physical and psychological dimensions of patient care. This is particularly important for older males and individuals with low physical activity intensity, who may benefit from more proactive mental health interventions. This recommendation is consistent with the integrated management model for patients with COPD proposed by Yohannes and Alexopoulos (2014). Lastly, network analysis has provided fresh insights into network-based precision interventions in clinical practice. The symptom “depressed” as the core symptom in the network suggests the necessity for clinicians to focus intensely on patients’ depressive states and recognize their potential role in initiating or intensifying other health issues. Additionally, targeted interventions can be designed based on the robust associations between various factors and specific depressive symptoms (such as GS with “exhausted” and “unhappy” and sleep duration with “lonely”). For example, in patients with diminished GS, an integrated approach involving both physical rehabilitation and psychological support could be employed to simultaneously alleviate fatigue and improve emotional well-being.

Despite the promising insights this study provides, it is important to recognize its limitations. As a cross-sectional study, this study cannot ascertain causal relationships between GS, sleep duration, CCDs, and depressive symptoms, which may have a bidirectional pattern. For instance, depressive symptoms might impair sleep quality, which in turn could exacerbate depressive symptoms. Furthermore, despite the adjustment for numerous potential confounders, unmeasured confounding variables could still affect the results. Factors such as social support, economic status, and the severity of the disease may influence the risk of depression in patients with CLDs. Future research should aim to overcome these limitations by employing longitudinal cohort studies to investigate the long-term effects of GS, sleep quality, and CCDs on depressive symptoms in patients with CLDs. The development and meticulous evaluation of intervention strategies derived from this study’s outcomes, such as integrated programs combining GS training and psychological support, could substantially aid in the prevention and amelioration of depression. It is imperative to delineate the biological underpinnings that link GS, sleep duration, and CCDs with depressive symptoms through inflammatory responses, oxidative stress, or neuroendocrine pathways. Advanced network analysis techniques, such as time-series network analysis, could shed light on the dynamic interactions between depressive symptoms and related influencing factors. Multicenter and cross-cultural studies are necessary to validate the applicability of these findings in diverse populations and healthcare systems, ensuring their relevance and utility across different contexts.

Therefore, this study unveiled the intricate associations of GS, sleep duration, and CCDs with depressive symptoms in patients with CLDs. These findings offer new insights and potential intervention targets to manage the psychological health of this vulnerable population. Future research should focus on clarifying the causal mechanisms underlying these relationships and on developing evidence-based, individualized intervention strategies to enhance mental health and overall quality of life for patients with CLDs.

This research contributes to the understanding of the interplay between physical health and psychological well-being in patients with CLDs and highlights significant implications for clinical practice and patient care. The identification of GS and sleep duration as potential modifiable risk factors suggests avenues for clinical intervention that could mitigate depressive symptoms in patients with CLDs. Future research should focus on longitudinal studies and diverse populations to validate these findings and develop effective, evidence-based interventions.