Linking Adverse Childhood Experiences and Chronic Lung Diseases: The Mediating Role of Depression, Frailty, and Social Isolation

Linking Adverse Childhood Experiences and Chronic Lung Diseases: The Mediating Role of Depression, Frailty, and Social Isolation | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Linking Adverse Childhood Experiences and Chronic Lung Diseases: The Mediating Role of Depression, Frailty, and Social Isolation Shuangwei Dong, Junpei Cai, Xiaoning Zhang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7514546/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 8 You are reading this latest preprint version Abstract Objectives This study examined the association from Chronic lung diseases (CLDs) to Adverse childhood experiences (ACEs) with a specific focus on examining the potential mediating effects of depression, frailty, and social isolation. Methods Data for this retrospective cohort study were obtained from participants enrolled in the China Health and Retirement Longitudinal Study (CHARLS). This study estimated competing structural equation model (SEM) examining the associations from ACEs to CLDs, and the mediating roles of depressive, frailty and social isolation. Results This study found ACEs had significant direct ( β = 0.024, p < 0.001), and total ( β = 0.034, p = 0.003) effects on CLDs. ACEs had a significant indirect effect on CLDs through depression (β = 0.009, p < 0.001), through Isolation (β = 0.003, p = 0.809). ACEs exerted multi-step indirect effects on CLDs through various pathways. ACEs influenced CLDs indirectly through both Depression and Frailty (β < 0.001, p < 0.001), through Depression and Isolation (β < 0.001, p = 0.809), through Isolation and Frailty (β < 0.001, p = 0.013). ACEs had a multi-step indirect effect on CLDs through Depression, Frailty, and Isolation (β < 0.001, p = 0.024). Conclusions This study establishes a significant association between ACEs and CLDs, in the elderly population. Furthermore, depression, frailty and social isolation as three mediating factors in the ACEs and CLDs relationship. Adverse childhood experiences Chronic lung diseases Mediating effect Figures Figure 1 Figure 2 Figure 3 Introduction Chronic lung diseases (CLDs), which include a range of airway and pulmonary disorders, and are among the leading causes of global mortality and morbidity ("GBD 2017: a fragile world," 2018). CLDs were ranked as the third leading cause of mortality worldwide, as highlighted by the Global Status Report on Noncommunicable Diseases in 2012(Zhou et al., 2016) and the Global Burden of Disease in 2019(Momtazmanesh et al., 2023). In China, the aging population exacerbated the burden of CLDs (Tian et al., 2019). Evidence suggests that the origins of CLDs in later life may be traced back to adverse exposures during early development(Gluckman et al., 2008), underscoring the importance of a life course perspective in understanding the origins of CLDs.(Duijts et al., 2014). Adverse Childhood Experiences (ACEs) refer to a constellation of traumatic exposures during childhood, including abuse, violence, and parental neglect, which have been empirically demonstrated to exert multisystemic and lifelong detrimental effects on human development (Sheridan & McLaughlin, 2014). A study conducted in China found that 66.2% of participants reported experiencing at least one ACE, and 5.9% reported experiencing four or more ACEs (Chang et al., 2019). Grounded in life course theory, ACEs are posited to influence adult health through both direct and indirect pathways, contributing to a wide spectrum of chronic conditions across the lifespan (Liu et al., 2025). Research has shown that a 10% reduction in the prevalence of ACEs could avert 3 million disability-adjusted life years (Bellis et al., 2019). With regard to respiratory health, ACEs have been associated with a wide range of long-term adverse outcomes, including increased risk of chronic obstructive pulmonary disease (COPD)(Merrick et al., 2019), asthma(Lin et al., 2021), chronic bronchitis(Duan et al., 2021). The mechanisms underlying the ACEs-CLDs relationship remain incompletely understood, but several mediating factors have been proposed. Frailty which may serve as an important pathway linking ACEs to the development of CLDs is defined as a state of increased vulnerability to stressors due to diminished reserves across multiple physiological systems (He et al., 2024). Previous studies have shown that ACEs are associated with multidimensional frailty in general (Schmahl et al., 2021), and older Chinese adults are particularly vulnerable to expanded ACEs (Wang, 2022). Depression, a prevalent mental health disorder linked to ACEs in adulthood, may further exacerbate this relationship by impairing psychosocial functioning and quality of life (Malhi & Mann, 2018; Poole et al., 2017). Social isolation is a multidimensional construct, often conflated with loneliness with the two terms frequently used interchangeably (Chen & Schulz, 2016). AACEs have been shown to contribute to increased social isolation in later life (Chen & Schulz, 2016). Prior research has indicated that social isolation in adulthood may result from the cumulative effects of ACEs (Choi & Hwang, 2023). These factors may interact synergistically. One study suggested that diminished social networks among the oldest adults may result from impairments in the physical and mental capacities required for social engagement (Domènech-Abella et al., 2019). Using participants without depression as the reference group, individuals with depression were found to have an increased risk of frailty (Soysal et al., 2017). Higher baseline loneliness in older adults may create a vicious cycle, contributing to early changes in frailty and subsequently leading to later increases in loneliness (Sha et al., 2022). Frailty may still be relevant for patients with age-related chronic diseases which can be regarded as a final common pathway leading to premature death from CLDs (Voshaar et al., 2021). The relation between physical health and the severity of depression is bidirectional, and older adults with CLDs exhibit both higher levels of depressive symptoms and poorer physical health (Steptoe et al., 2015). Social isolation heightens the risk of winter hospitalization for individuals with COPD thereby contributing to the overall burden of chronic lung disease in the elderly (Meng et al., 2024). Existing research has focused on the link between ACEs and specific CLDs without exploring the potential underlying pathways; as a result, the mechanisms remain poorly understood and warrant further investigation. Based on the aforementioned theoretical propositions, this study developed a conceptual framework and employed structural equation modeling (SEM) to examine the hypothesized relationships among the constructs within the proposed framework. This study aims to investigate the relationship between ACEs and CLDs, with a specific focus on the potential mediating effects of depression, frailty, and social isolation, using SEM to validate these associations. Understanding this relationship provides crucial evidence for the comprehensive prevention of CLDs. Methods Study participants The data for this study were obtained from the China Health and Retirement Longitudinal Study (CHARLS) conducted in 2011 and the Life History Survey conducted in 2014, both of which are prospective, nationally representative cohort studies in China. Using a multistage, stratified, probability-proportional-to-size (PPS) sampling method, participants were randomly selected from 28 provinces, 150 counties, and 450 communities in China. All participants in the CHARLS provided written informed consent, and CHARLS was approved by the Ethical Review Committee of Peking University. Measurement Chronic lung diseases CLDs were assessed as a binary variable based on self-reported diagnoses. Participants responded to the question in the questionnaire: Have you been diagnosed with Chronic lung diseases, such as chronic bronchitis, emphysema (excluding tumors or cancer)? “1” indicates that the participant has been diagnosed with CLDs, whereas “0” indicates not.(Li et al., 2024). Adverse childhood experiences Ten ACE indicators were evaluated, categorized into household substance abuse, unsafe neighborhood, physical abuse, domestic violence, and bullying, emotional abuse, incarcerated household member, neglect, household mental illness and parental separation, divorce or death (Lin et al., 2022). Each indicator was dichotomized, with 0 indicating absence and 1 indicating presence. A cumulative ACE score was calculated by summing the ACEs experienced by each participant, with those reporting ≥ 2 ACEs coded as 1 and those reporting < 2 ACEs coded as 0 (Liu et al., 2024). Frailty Frailty was quantified using a frailty index (FI) following standard procedures described previously (He et al., 2023; Rockwood, 2008). The FI was calculated based on the accumulation of multiple age-related health deficits, including diseases (excluding chronic lung disease), symptoms, disabilities, and physical function, using data from CHARLS. Items 1–25 were dichotomized as 1 (presence of the deficit) or 0 (absence of the deficit) according to the corresponding cut-off values. The cognitive score (item 26) was a continuous variable ranging from 0 to 1, with higher scores indicating worse cognitive function. The FI, also ranging from 0 to 1, was calculated as the mean of deficits present for each participant. with higher values indicating greater levels of frailty. Depression The Center for Epidemiologic Studies Depression Scale (CESD) is a self-report rating scale developed by Radloff in 1977 to assess current depressive symptoms in primary care settings(Boey, 1999). The CESD is a 10-item scale. For each item, participants reported the frequency of occurrence during the past week. Each item was scored on a 4-point scales: rarely or none of the time (≤ 1 day per week) = 0, some or a little of the time (1–2 days per week) = 1, occasionally or a moderate amount of the time (3–4 days per week) = 2, and most or all of the time (5–7 days per week) = 3. The total score ranges from 0 to 30, with higher scores indicating more severe depressive symptoms. Social Isolation A composite index of social isolation was constructed based on participants’ social networks and social activity or engagement during the 2011 baseline survey(Nicholson, 2009). The index comprises four indicators: living alone, being currently unmarried, having contact with children less than once a week, and participating in social activities less than once a month (Yu et al., 2021). Each item was scored as 1 or 0. A total social isolation score ranging from 0 to 4 was calculated by summing these indicators, with higher scores indicating greater level of social isolation. Covariates This study also considered sociodemographic characteristics and health-related factors. Sociodemographic characteristics included age, gender, and education. Health-related factors included smoking and drinking status. Smoking status was categorized as never smokers and ever smokers, with ever smokers including both former and current smokers. Drinking status was classified into three levels: drink more than once a month, drink less than once a month and none of these. Education was categorized into three levels: below high school, high school, and college or above. Statistical analysis Continuous variables were presented as mean with standard deviation (SD), whereas categorical variables were presented as frequencies and percentages. Independent-samples t-tests was used to compare continuous variables, and chi-square test was used to compare categorical variables. Spearman correlation analysis was used to examine the correlations among CLDs, ACEs, depression, frailty, social isolation and Covariates. Additionally, geospatial visualization was employed to map the distributions of CLDs and ACEs onto China’s administrative division maps in order to analyze their regional patterns. The hypothesized model was tested using structural equation modeling (SEM). Maximum Likelihood (ML) estimation was used to assess the pathways between ACEs and CLDs and to separate the associations into direct and indirect effects(Chen et al., 2024). Before conducting mediation analyses, missing data were handled using full information maximum likelihood (FIML) estimation (Chen et al., 2024). Model fit was evaluated using several fit indices, including the Chi-square test, Comparative Fit Index (CFI), Root Mean Square Error of Approximation (RMSEA), and Standardized Root Mean Square Residual (SRMR). Three sets of sensitivity analyses were performed. All data analysis and visualization procedures were conducted using the statistical R. version 4.4.2, and a two-sided p < 0.05 was considered statistically significant. Result Characteristics of participants As show on Table 1 , a total of 17496 participants were included in this study, of whom 1,781 had CLDs and 15,715 did not. The mean age of participants was 59.0 ± 10.1 years. The majority of participants were female (52.5%) and had middle school education or below (87.3%). Among them, 60.5% had never smoked and 67.1% had not consumed any alcoholic beverages in the past year. The mean scores for frailty index, social isolation and depression were 0.252 (0.102), 1.8 (0.7) and 10.0 (4.9), respectively. Gender, education and smoking were significantly associated with CLDs, whereas drinking status was not. The study also revealed distinct geographical patterns in disease distribution: Western China exhibited higher prevalence rates of CLDs, while southern regions demonstrated elevated incidence of ACEs. The regional distributions of ACEs and CLDs prevalence rates are presented in Fig. 1 . Table 1 Sociodemographic differences between CLD ( N = 17496) Variables Total Number of CLD p No ( n = 15715) Yes ( n = 1781) X 2 /t Age Mean (SD) 59.0(10.1) 58.6(10.0) 62.7(10.3) -6.828 < 0.001 Gender n % 38.832 < 0.001 Male 6771(47.2) 5972(46.3) 799(54.9) Female 7579 (52.8) 6924(53.7) 655(45.1) Education n % 32.315 < 0.001 Middle school or below 15255 (87.3) 13635(86.9) 1620(91.2) High school 1366(7.8) 1286(8.2) 80(4.5) College/university or above 849(4.9) 772(4.9) 77(4.3) Smoking n % 124.345 < 0.001 Yes 6902(39.5) 5981(38.1) 921(51.8) No 10574(60.5) 9716(61.9) 858(48.2) Drinking n % 4.568 0.102 Drink more than once a month 4365(25.0) 3924(25.0) 441(24.8) Drink but less than once a month 1377(7.9) 1259(8.0) 118(6.6) None of these 11728(67.1) 10508(67.0) 1220(68.6) Adverse childhood experiences n % 8.099 0.004 Yes 3793(48.9) 3344(48.3) 449(53.6) No 3967(51.1) 3578(51.7) 389(46.4) Frailty Mean (SD) 0.252(0.102) 0.249(0.102) 0.276(0.102) -6.780 < 0.001 Social isolation Mean (SD) 1.8(0.7) 1.7.(0.7) 1.8(0.7) -1.565 0.118 Depression Mean (SD) 10.0(4.9) 9.9(4.9) 11.4(5.2) -5.310 < 0.001 Notes . CLD: chronic lung disease Table 2 Descriptive statistics and correlations of ACEs, Frailty, Social isolation, Depression, CLD and sociodemographic characteristics ( N = 17496). Mean SD 1 2 3 4 5 6 7 8 9 10 1 Age 59.045 10.148 1 2 gender 1.528 0.499 − 0.069** 1 3 Education 1.175 0.491 − 0.140** − 0.124** 1 4 Smoking 1.605 0.488 − 0.069** 0.677** − 0.030** 1 5 Drinking 2.421 0.862 0.050** 0.484** − 0.075** 0.415** 1 6 ACEs 0.489 0.499 0.010 0.124** − 0.101** 0.076** 0.049** 1 7 frailty 0.252 0.102 0.039** 0.020 0.062** 0.011 0.059** − 0.006 1 8 social isolation 1.751 0.699 0.099** 0.069** − 0.070** 0.031* 0.039** 0.100** − 0.029* 1 9 Depression 10.004 4.872 0.045** 0.166** − 0.115** 0.085** 0.091** 0.140** 0.186** 0.084** 1 10 CLD 0.108 0.302 0.122** − 0.052** − 0.038** -0.085** 0.008 0.033* 0.087** 0.026* 0.092** 1 Note. SD, standard deviation. * p < .05, *** p < .001. ACEs, Adverse childhood experience; CLD, chronic lung disease. Correlation Between Variables CLDs was positively correlated with ACEs ( r = 0.033, p = 0.004), frailty ( r = 0.087, p < 0.001), social isolation ( r = 0.026, p = 0.01), and depression ( r = 0.092, p < 0.001). ACEs was positively correlated with social isolation ( r = 0.100, p < 0.001) and depression ( r = 0.140, p < 0.001). Frailty was positively correlated with depression ( r = 0.186, p < 0.001) and negatively correlated with social isolation ( r = -0.029, p = 0.019). Social isolation was positively correlated with depression ( r = 0.083, p < 0.001). Structural equation modeling analysis This study examined a structural relationship among ACEs, depression, frailty, social isolation, and CLD. The hypothesized model controlling for all Covariates, demonstrated an excellent fit: CFI = 0.997, TLI = 0.917, RMSEA = 0.019 and SRMR = 0.003. Specifically, ACEs were positively associated with CLDs (β = 0.024, P < 0.05), depression symptoms (β = 0.117, P < 0.001), and social isolation (β = 0.077, P < 0.001); social isolation was negatively associated with frailty (β = -0.071, P < 0.001), depression symptoms were positively associated with frailty (β = 0.217, P < 0.001), social isolation (β = 0.060, P < 0.001), and CLDs (β = 0.078, P < 0.001); and frailty was positively associated with CLDs (β = 0.058, P < 0.001). As shown in Table 3 , the total standardized effect of ACEs on CLDs was 0.34, while the direct standardized effect was 0.24. In addition to total and direct effects, the indirect effects of ACEs on CLDs were examined through depression symptoms, social isolation, and frailty. ACEs had a significant indirect effect on CLDs via depression (β = 0.009, p < 0.001). In contrast, the indirect effect of ACEs on CLDs via social isolation was not statistically significant (β = 0.003, p = 0.809). ACEs also exerted multi-step indirect effects on CLDs through different pathways: via both depression and frailty (β < 0.001, p < 0.001); via depression and social isolation (β < 0.001, p = 0.809); via social isolation and frailty (β < 0.001, p = 0.013); and through depression, frailty, and social isolation simultaneously (β < 0.001, p = 0.024). Table 3 Standardized effects of ACEs on CLD through social isolation, depression and frailty ( N = 17496) B 95%CI β SE CR p ACEs → Depression → CLD 0.006 0.004 0.008 0.009 0.001 5.294 < 0.001 ACEs → Social isolation → CLD < 0.001 − 0.001 0.002 < 0.001 0.001 0.242 0.809 ACEs → Depression → Frailty → CLD 0.001 < 0.001 0.001 0.001 < 0.001 3.881 < 0.001 ACEs → Depression → Social isolation → CLD < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 0.242 0.809 ACEs → Social isolation → Frailty → CLD < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 − 2.489 0.013 ACEs → Depression → Frailty → Social isolation → CLD < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 − 2.256 0.024 Total Indirect 0.007 0.004 0.009 0.011 0.001 5.052 < 0.001 Total Direct 0.015 0.001 0.029 0.024 0.007 2.072 0.038 Total Effect 0.021 0.007 0.035 0.034 0.007 3.017 0.003 Note. CR , critical ratio ; SE , standard error; ACEs, Adverse childhood experience; CLD, chronic lung disease. Sensitivity analyses Three sensitivity analyses were conducted, and results are presented in Supplementary Table s1 -6. Covariates were categorized into two distinct groups—demographic variables and health-related measures—and were incorporated separately into the analytical models. Mediation analyses were repeated after excluding participants with missing ACEs data. The results of these sensitivity analyses were consistent with the main findings, supporting the robustness of our conclusions. Discussion The results indicated that ACEs were associated with CLDs, that mirrors previous research on the association between general ACEs and CLDs (Anda et al., 2008; Li et al., 2024). However, how ACEs affect CLDs remains unclear. According to the extant literature, the physiopathological mechanisms underlying the relationship between ACE and the aetiology of various chronic diseases likely involve organic responses to chronic psychosocial stress (Lopes et al., 2020). Exposure to traumatic stress during childhood can lead to lasting alterations in the central nervous system, including heightened activity of the hypothalamic–pituitary–adrenal (HPA) axis (Bremner, 2001). This may affect both lung development during childhood and adolescence and the functioning of the cardiorespiratory system across the lifespan (Anda et al., 2008). On the other hand, maternal exposure to a hostile environment and the resulting stress response may induce maternal system inflammation or fetal inflammation (Ji et al., 2021). The mediation analysis indicated that both depression and frailty served as mediators in the association between ACEs and CLDs. These observed mediating effects may operate through two potential mechanisms. One potential mechanism involves ACEs inducing persistent, long-term inflammatory responses in the body (Heard-Garris et al., 2020). Chronic inflammation can damage pulmonary tissues and impair the nervous system, potentially contributing to the development of depression, frailty, and, ultimately CLDs(Lee & Giuliani, 2019; Soysal et al., 2016). Another potential mechanism is that ACEs leave lasting psychological scars (Choi & Hwang, 2023), which may contribute to depression in adulthood. This condition can, in turn, lead to heightened feelings of stigma and shame, thereby reducing health-related quality of life (Suen et al., 2023). Frailty and poor psychological well-being are strongly correlated(Andrew et al., 2012). The accumulation of health deficits in older adults may create a self-perpetuating cycle of decline termed a"frailty identity crisis", in which perceived physical limitations reinforce psychological distress (Andrew et al., 2012). The findings also revealed that, while social isolation alone did not a direct effect on CLDs, it exerted a significant effect when combined with frailty. Social isolation by itself does not directly cause CLDs in older adults, which represents certain discrepancies with previous studies (Stoustrup et al., 2024). This discrepancy may stem from distinct sociocultural contexts. Specifically, the unique historical experiences of China's middle-aged and older adult, shaped by the One-Child Policy and economic hardships, has producted a generation with lower reliance on social welfare systems. However, when combined with frailty, social isolation produces a harmful synergy that significantly elevates the risk of CLDs. This interaction effect primarily occurs through limited access to healthcare services: frail individuals who are socially isolated face compounded barriers to medical care, preventive care, and necessary social support (Donovan & Blazer, 2020). Consequently, this dual burden of physical frailty and limited access to healthcare further exacerbates pulmonary vulnerability, resulting in greater susceptibility to respiratory infections and accelerated disease progression. The geospatial analysis revealed distinct regional patterns: ACEs exposure was markedly higher in southern provinces, whereas the prevalence of CLDs was more pronounced in central-western regions. This epidemiological distribution may be attributed to inadequate healthcare infrastructure combined with region-specific climatic factors, including persistent humidity in the south and arid, dust storm-prone conditions in the central-west. More importantly, lower familial socioeconomic status emerged as a key determinant, as indicated by substantially lower disease rates in the more economically developed southeastern provinces. Several limitations of this study warrant discussion. First, the definition of CLDs in this study was based solely on participants’ self-reported data, without corresponding medical diagnoses available in the CHARLS database. Second, data on threat-related ACEs relied on retrospective self-reporting, which may introduce recall bias. Conclusion The study confirms the significant relationship between ACEs and CLDs, as well as their mediation through depression, frailty, and social isolation using structural equation modeling, while also examining China-specific geographical patterns in ACEs distribution. These findings provide crucial evidence for implementing comprehensive CLDs prevention programs that adopt a life-course perspective and incorporate biopsychosocial elements. Abbreviations CHARLS China Health and Retirement Longitudinal Study CLDs Chronic lung diseases ACEs Adverse Childhood Experiences FI frailty index CESD The Center for Epidemiologic Studies Depression Scale. Declarations Ethics approval and consent to participate Ethics approval for the study was granted by the Ethics Review Committee of Peking University, and all the participants provided signed informed consent at the time of participation. The study methodology was carried out in accordance with approved guidelines. Consent for publication Not applicable Availability of data and materials The dataset collected and analyzed in the current study are available from the corresponding author on reasonable request Competing interests The authors declare that there are no conflicts of interest Funding This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Authors’ contributions All authors (Shuangwei Dong, Junpei Cai, and Xiaoning Zhang) have made substantial contributions to: Study conception/design and data interpretation Drafting and critical revision of the manuscript Final approval of the submitted version Acknowledgements We are grateful to the China Center for Economic Research at Beijing University for providing us with the data, and we thank the CHARLS research and field team for collecting the data. References Anda, R. F., Brown, D. W., Dube, S. R., Bremner, J. D., Felitti, V. J., & Giles, W. H. (2008). Adverse childhood experiences and chronic obstructive pulmonary disease in adults [Article]. American Journal of Preventive Medicine , 34 (5), 396-403. https://doi.org/10.1016/j.amepre.2008.02.002 Andrew, M. K., Fisk, J. D., & Rockwood, K. (2012). Psychological well-being in relation to frailty: a frailty identity crisis? [Article]. 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06:49:33","extension":"html","order_by":15,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":117982,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7514546/v1/770909ee35143950797d82bf.html"},{"id":91953528,"identity":"f3c3caf2-13d7-45ec-9c1f-b095f06ee3f6","added_by":"auto","created_at":"2025-09-23 06:57:32","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":115606,"visible":true,"origin":"","legend":"\u003cp\u003edistribution of adverse childhood experiences and chronic lung diseasein China\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7514546/v1/cddf24c7555488e7ed7d3208.png"},{"id":91953531,"identity":"65a2c8a2-7183-4d1f-a40c-10f1efc15db4","added_by":"auto","created_at":"2025-09-23 06:57:32","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":33083,"visible":true,"origin":"","legend":"\u003cp\u003eConceptual framework and hypotheses\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eNotes. \u003c/em\u003eACEs, Adverse childhood experiences; CLD,Chronic lung disease, Isolation, Social isolation.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7514546/v1/03322d316f66d05d3d0ac7d1.png"},{"id":91951951,"identity":"b8473aa5-ee1a-4e84-83b9-169b1f505d3f","added_by":"auto","created_at":"2025-09-23 06:49:32","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":43959,"visible":true,"origin":"","legend":"\u003cp\u003eThe standardized direct effects of ACEs on CLD through depression, isolation and frailty\u003c/p\u003e\n\u003cp\u003e(Model fit: CFI=0.997 TLI=0.917 RMSEA=0.019 and SRMR=0.003)\u003c/p\u003e\n\u003cp\u003e. *\u003cem\u003ep \u003c/em\u003e\u0026lt; 0.05, **\u003cem\u003ep \u003c/em\u003e\u0026lt; 0.001\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eNotes. \u003c/em\u003eACEs, Adverse childhood experiences; CLD, Chronic lung disease, Isolation, Social isolation.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7514546/v1/5e6232bb64e9411045ab90bc.png"},{"id":91956932,"identity":"a835c514-b976-44c3-baf5-1ee240adab67","added_by":"auto","created_at":"2025-09-23 07:21:33","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1474467,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7514546/v1/8c909769-ce57-4e44-98b2-74f765bee31f.pdf"},{"id":91954002,"identity":"0530d7bf-4d86-4a8d-9005-59c61d2b5a1e","added_by":"auto","created_at":"2025-09-23 07:05:32","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":29360,"visible":true,"origin":"","legend":"","description":"","filename":"table.docx","url":"https://assets-eu.researchsquare.com/files/rs-7514546/v1/ce52de900f7b25daf0f68847.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Linking Adverse Childhood Experiences and Chronic Lung Diseases: The Mediating Role of Depression, Frailty, and Social Isolation","fulltext":[{"header":"Introduction","content":"\u003cp\u003eChronic lung diseases (CLDs), which include a range of airway and pulmonary disorders, and are among the leading causes of global mortality and morbidity (\"GBD 2017: a fragile world,\" 2018). CLDs were ranked as the third leading cause of mortality worldwide, as highlighted by the Global Status Report on Noncommunicable Diseases in 2012(Zhou et al., 2016) and the Global Burden of Disease in 2019(Momtazmanesh et al., 2023). In China, the aging population exacerbated the burden of CLDs (Tian et al., 2019). Evidence suggests that the origins of CLDs in later life may be traced back to adverse exposures during early development(Gluckman et al., 2008), underscoring the importance of a life course perspective in understanding the origins of CLDs.(Duijts et al., 2014).\u003c/p\u003e\u003cp\u003eAdverse Childhood Experiences (ACEs) refer to a constellation of traumatic exposures during childhood, including abuse, violence, and parental neglect, which have been empirically demonstrated to exert multisystemic and lifelong detrimental effects on human development (Sheridan \u0026amp; McLaughlin, 2014). A study conducted in China found that 66.2% of participants reported experiencing at least one ACE, and 5.9% reported experiencing four or more ACEs (Chang et al., 2019). Grounded in life course theory, ACEs are posited to influence adult health through both direct and indirect pathways, contributing to a wide spectrum of chronic conditions across the lifespan (Liu et al., 2025). Research has shown that a 10% reduction in the prevalence of ACEs could avert 3\u0026nbsp;million disability-adjusted life years (Bellis et al., 2019). With regard to respiratory health, ACEs have been associated with a wide range of long-term adverse outcomes, including increased risk of chronic obstructive pulmonary disease (COPD)(Merrick et al., 2019), asthma(Lin et al., 2021), chronic bronchitis(Duan et al., 2021).\u003c/p\u003e\u003cp\u003eThe mechanisms underlying the ACEs-CLDs relationship remain incompletely understood, but several mediating factors have been proposed. Frailty which may serve as an important pathway linking ACEs to the development of CLDs is defined as a state of increased vulnerability to stressors due to diminished reserves across multiple physiological systems (He et al., 2024). Previous studies have shown that ACEs are associated with multidimensional frailty in general (Schmahl et al., 2021), and older Chinese adults are particularly vulnerable to expanded ACEs (Wang, 2022). Depression, a prevalent mental health disorder linked to ACEs in adulthood, may further exacerbate this relationship by impairing psychosocial functioning and quality of life (Malhi \u0026amp; Mann, 2018; Poole et al., 2017). Social isolation is a multidimensional construct, often conflated with loneliness with the two terms frequently used interchangeably (Chen \u0026amp; Schulz, 2016). AACEs have been shown to contribute to increased social isolation in later life (Chen \u0026amp; Schulz, 2016). Prior research has indicated that social isolation in adulthood may result from the cumulative effects of ACEs (Choi \u0026amp; Hwang, 2023). These factors may interact synergistically. One study suggested that diminished social networks among the oldest adults may result from impairments in the physical and mental capacities required for social engagement (Dom\u0026egrave;nech-Abella et al., 2019). Using participants without depression as the reference group, individuals with depression were found to have an increased risk of frailty (Soysal et al., 2017). Higher baseline loneliness in older adults may create a vicious cycle, contributing to early changes in frailty and subsequently leading to later increases in loneliness (Sha et al., 2022). Frailty may still be relevant for patients with age-related chronic diseases which can be regarded as a final common pathway leading to premature death from CLDs (Voshaar et al., 2021). The relation between physical health and the severity of depression is bidirectional, and older adults with CLDs exhibit both higher levels of depressive symptoms and poorer physical health (Steptoe et al., 2015). Social isolation heightens the risk of winter hospitalization for individuals with COPD thereby contributing to the overall burden of chronic lung disease in the elderly (Meng et al., 2024).\u003c/p\u003e\u003cp\u003eExisting research has focused on the link between ACEs and specific CLDs without exploring the potential underlying pathways; as a result, the mechanisms remain poorly understood and warrant further investigation. Based on the aforementioned theoretical propositions, this study developed a conceptual framework and employed structural equation modeling (SEM) to examine the hypothesized relationships among the constructs within the proposed framework.\u003c/p\u003e\u003cp\u003eThis study aims to investigate the relationship between ACEs and CLDs, with a specific focus on the potential mediating effects of depression, frailty, and social isolation, using SEM to validate these associations. Understanding this relationship provides crucial evidence for the comprehensive prevention of CLDs.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy participants\u003c/h2\u003e\u003cp\u003eThe data for this study were obtained from the China Health and Retirement Longitudinal Study (CHARLS) conducted in 2011 and the Life History Survey conducted in 2014, both of which are prospective, nationally representative cohort studies in China. Using a multistage, stratified, probability-proportional-to-size (PPS) sampling method, participants were randomly selected from 28 provinces, 150 counties, and 450 communities in China. All participants in the CHARLS provided written informed consent, and CHARLS was approved by the Ethical Review Committee of Peking University.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eMeasurement\u003c/h3\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003eChronic lung diseases\u003c/h2\u003e\u003cp\u003eCLDs were assessed as a binary variable based on self-reported diagnoses. Participants responded to the question in the questionnaire: Have you been diagnosed with Chronic lung diseases, such as chronic bronchitis, emphysema (excluding tumors or cancer)? “1” indicates that the participant has been diagnosed with CLDs, whereas “0” indicates not.(Li et al., 2024).\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eAdverse childhood experiences\u003c/h3\u003e\n\u003cp\u003eTen ACE indicators were evaluated, categorized into household substance abuse, unsafe neighborhood, physical abuse, domestic violence, and bullying, emotional abuse, incarcerated household member, neglect, household mental illness and parental separation, divorce or death (Lin et al., 2022). Each indicator was dichotomized, with 0 indicating absence and 1 indicating presence. A cumulative ACE score was calculated by summing the ACEs experienced by each participant, with those reporting ≥ 2 ACEs coded as 1 and those reporting \u0026lt; 2 ACEs coded as 0 (Liu et al., 2024).\u003c/p\u003e\n\u003ch3\u003eFrailty\u003c/h3\u003e\n\u003cp\u003eFrailty was quantified using a frailty index (FI) following standard procedures described previously (He et al., 2023; Rockwood, 2008). The FI was calculated based on the accumulation of multiple age-related health deficits, including diseases (excluding chronic lung disease), symptoms, disabilities, and physical function, using data from CHARLS. Items 1–25 were dichotomized as 1 (presence of the deficit) or 0 (absence of the deficit) according to the corresponding cut-off values. The cognitive score (item 26) was a continuous variable ranging from 0 to 1, with higher scores indicating worse cognitive function. The FI, also ranging from 0 to 1, was calculated as the mean of deficits present for each participant. with higher values indicating greater levels of frailty.\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eDepression\u003c/h2\u003e\u003cp\u003eThe Center for Epidemiologic Studies Depression Scale (CESD) is a self-report rating scale developed by Radloff in 1977 to assess current depressive symptoms in primary care settings(Boey, 1999). The CESD is a 10-item scale. For each item, participants reported the frequency of occurrence during the past week. Each item was scored on a 4-point scales: rarely or none of the time (≤ 1 day per week) = 0, some or a little of the time (1–2 days per week) = 1, occasionally or a moderate amount of the time (3–4 days per week) = 2, and most or all of the time (5–7 days per week) = 3. The total score ranges from 0 to 30, with higher scores indicating more severe depressive symptoms.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eSocial Isolation\u003c/h3\u003e\n\u003cp\u003eA composite index of social isolation was constructed based on participants’ social networks and social activity or engagement during the 2011 baseline survey(Nicholson, 2009). The index comprises four indicators: living alone, being currently unmarried, having contact with children less than once a week, and participating in social activities less than once a month (Yu et al., 2021). Each item was scored as 1 or 0. A total social isolation score ranging from 0 to 4 was calculated by summing these indicators, with higher scores indicating greater level of social isolation.\u003c/p\u003e\n\u003ch3\u003eCovariates\u003c/h3\u003e\n\u003cp\u003eThis study also considered sociodemographic characteristics and health-related factors. Sociodemographic characteristics included age, gender, and education. Health-related factors included smoking and drinking status. Smoking status was categorized as never smokers and ever smokers, with ever smokers including both former and current smokers. Drinking status was classified into three levels: drink more than once a month, drink less than once a month and none of these. Education was categorized into three levels: below high school, high school, and college or above.\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eContinuous variables were presented as mean with standard deviation (SD), whereas categorical variables were presented as frequencies and percentages. Independent-samples t-tests was used to compare continuous variables, and chi-square test was used to compare categorical variables. Spearman correlation analysis was used to examine the correlations among CLDs, ACEs, depression, frailty, social isolation and Covariates. Additionally, geospatial visualization was employed to map the distributions of CLDs and ACEs onto China’s administrative division maps in order to analyze their regional patterns.\u003c/p\u003e\u003cp\u003eThe hypothesized model was tested using structural equation modeling (SEM). Maximum Likelihood (ML) estimation was used to assess the pathways between ACEs and CLDs and to separate the associations into direct and indirect effects(Chen et al., 2024). Before conducting mediation analyses, missing data were handled using full information maximum likelihood (FIML) estimation (Chen et al., 2024). Model fit was evaluated using several fit indices, including the Chi-square test, Comparative Fit Index (CFI), Root Mean Square Error of Approximation (RMSEA), and Standardized Root Mean Square Residual (SRMR). Three sets of sensitivity analyses were performed. All data analysis and visualization procedures were conducted using the statistical R. version 4.4.2, and a two-sided \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05 was considered statistically significant.\u003c/p\u003e\u003c/div\u003e"},{"header":"Result","content":"\u003ch2\u003eCharacteristics of participants\u003c/h2\u003e\u003cp\u003eAs show on Table\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, a total of 17496 participants were included in this study, of whom 1,781 had CLDs and 15,715 did not. The mean age of participants was 59.0 ± 10.1 years. The majority of participants were female (52.5%) and had middle school education or below (87.3%). Among them, 60.5% had never smoked and 67.1% had not consumed any alcoholic beverages in the past year. The mean scores for frailty index, social isolation and depression were 0.252 (0.102), 1.8 (0.7) and 10.0 (4.9), respectively. Gender, education and smoking were significantly associated with CLDs, whereas drinking status was not. The study also revealed distinct geographical patterns in disease distribution: Western China exhibited higher prevalence rates of CLDs, while southern regions demonstrated elevated incidence of ACEs. The regional distributions of ACEs and CLDs prevalence rates are presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSociodemographic differences between CLD (\u003cem\u003eN\u003c/em\u003e = 17496)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eVariables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003eNumber of CLD\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNo (\u003cem\u003en\u003c/em\u003e = 15715)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eYes (\u003cem\u003en\u003c/em\u003e = 1781)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003eX\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e/t\u003c/b\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAge Mean (SD)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e59.0(10.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e58.6(10.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e62.7(10.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-6.828\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eGender\u003c/b\u003e \u003cb\u003en\u003c/b\u003e \u003cb\u003e%\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e38.832\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6771(47.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5972(46.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e799(54.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e7579 (52.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e6924(53.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e655(45.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eEducation\u003c/b\u003e \u003cb\u003en %\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e32.315\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMiddle school or below\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e15255 (87.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e13635(86.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1620(91.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHigh school\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1366(7.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1286(8.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e80(4.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCollege/university or above\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e849(4.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e772(4.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e77(4.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSmoking\u003c/b\u003e \u003cb\u003en\u003c/b\u003e \u003cb\u003e%\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e124.345\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6902(39.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5981(38.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e921(51.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e10574(60.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e9716(61.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e858(48.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDrinking\u003c/b\u003e \u003cb\u003en %\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e4.568\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.102\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDrink more than once a month\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e4365(25.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3924(25.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e441(24.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDrink but less than once a month\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1377(7.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1259(8.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e118(6.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNone of these\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e11728(67.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e10508(67.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1220(68.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAdverse childhood experiences\u003c/b\u003e \u003cb\u003en %\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e8.099\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.004\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3793(48.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3344(48.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e449(53.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3967(51.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3578(51.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e389(46.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eFrailty Mean (SD)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.252(0.102)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.249(0.102)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.276(0.102)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-6.780\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSocial isolation Mean (SD)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.8(0.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.7.(0.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.8(0.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-1.565\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.118\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDepression Mean (SD)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e10.0(4.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e9.9(4.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e11.4(5.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-5.310\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003cem\u003eNotes\u003c/em\u003e. CLD: chronic lung disease\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003e\u003cb\u003eDescriptive statistics and correlations of ACEs, Frailty, Social isolation, Depression, CLD and sociodemographic characteristics (\u003c/b\u003e\u003cb\u003eN\u003c/b\u003e \u003cb\u003e= 17496).\u003c/b\u003e\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"14\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMean\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSD\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c10\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c11\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c12\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c13\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c14\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAge\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e59.045\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10.148\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003egender\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.528\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.499\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e− 0.069**\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003e3\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003eEducation\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e1.175\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0.491\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e− 0.140**\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e− 0.124**\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003e4\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003eSmoking\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e1.605\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0.488\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e− 0.069**\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.677**\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e− 0.030**\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003e5\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003eDrinking\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e2.421\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0.862\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.050**\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.484**\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e− 0.075**\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u003cb\u003e0.415**\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003e6\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003eACEs\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e0.489\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0.499\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.010\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.124**\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e− 0.101**\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u003cb\u003e0.076**\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u003cb\u003e0.049**\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003e7\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003efrailty\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e0.252\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0.102\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.039**\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.020\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e0.062**\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u003cb\u003e0.011\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u003cb\u003e0.059**\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u003cb\u003e− 0.006\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003e8\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003esocial isolation\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e1.751\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0.699\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.099**\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.069**\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e− 0.070**\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u003cb\u003e0.031*\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u003cb\u003e0.039**\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u003cb\u003e0.100**\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e\u003cb\u003e− 0.029*\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003e9\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003eDepression\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e10.004\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e4.872\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.045**\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.166**\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e− 0.115**\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u003cb\u003e0.085**\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u003cb\u003e0.091**\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u003cb\u003e0.140**\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e\u003cb\u003e0.186**\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e\u003cb\u003e0.084**\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003e10\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003eCLD\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e0.108\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0.302\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.122**\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e− 0.052**\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e− 0.038**\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u003cb\u003e-0.085**\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u003cb\u003e0.008\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u003cb\u003e0.033*\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e\u003cb\u003e0.087**\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e\u003cb\u003e0.026*\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e\u003cb\u003e0.092**\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e\u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"14\"\u003e\u003cem\u003eNote.\u003c/em\u003e SD, standard deviation. *\u003cem\u003ep\u003c/em\u003e \u0026lt; .05, ***\u003cem\u003ep\u003c/em\u003e \u0026lt; .001. ACEs, Adverse childhood experience; CLD, chronic lung disease.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003ch2\u003eCorrelation Between Variables\u003c/h2\u003e\u003cp\u003eCLDs was positively correlated with ACEs (\u003cem\u003er\u003c/em\u003e = 0.033, \u003cem\u003ep\u003c/em\u003e = 0.004), frailty (\u003cem\u003er\u003c/em\u003e = 0.087, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001), social isolation (\u003cem\u003er\u003c/em\u003e = 0.026, \u003cem\u003ep\u003c/em\u003e = 0.01), and depression (\u003cem\u003er\u003c/em\u003e = 0.092, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001). ACEs was positively correlated with social isolation (\u003cem\u003er\u003c/em\u003e = 0.100, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001) and depression (\u003cem\u003er\u003c/em\u003e = 0.140, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001). Frailty was positively correlated with depression (\u003cem\u003er\u003c/em\u003e = 0.186, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001) and negatively correlated with social isolation (\u003cem\u003er\u003c/em\u003e = -0.029, \u003cem\u003ep\u003c/em\u003e = 0.019). Social isolation was positively correlated with depression (\u003cem\u003er\u003c/em\u003e = 0.083, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001).\u003c/p\u003e\u003ch2\u003eStructural equation modeling analysis\u003c/h2\u003e\u003cp\u003eThis study examined a structural relationship among ACEs, depression, frailty, social isolation, and CLD. The hypothesized model controlling for all Covariates, demonstrated an excellent fit: CFI = 0.997, TLI = 0.917, RMSEA = 0.019 and SRMR = 0.003. Specifically, ACEs were positively associated with CLDs (β = 0.024, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05), depression symptoms (β = 0.117, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001), and social isolation (β = 0.077, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001); social isolation was negatively associated with frailty (β = -0.071, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001), depression symptoms were positively associated with frailty (β = 0.217, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001), social isolation (β = 0.060, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001), and CLDs (β = 0.078, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001); and frailty was positively associated with CLDs (β = 0.058, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001).\u003c/p\u003e\u003cp\u003eAs shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, the total standardized effect of ACEs on CLDs was 0.34, while the direct standardized effect was 0.24. In addition to total and direct effects, the indirect effects of ACEs on CLDs were examined through depression symptoms, social isolation, and frailty. ACEs had a significant indirect effect on CLDs via depression (β = 0.009, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001). In contrast, the indirect effect of ACEs on CLDs via social isolation was not statistically significant (β = 0.003, p = 0.809). ACEs also exerted multi-step indirect effects on CLDs through different pathways: via both depression and frailty (β \u0026lt; 0.001, p \u0026lt; 0.001); via depression and social isolation (β \u0026lt; 0.001, p = 0.809); via social isolation and frailty (β \u0026lt; 0.001, p = 0.013); and through depression, frailty, and social isolation simultaneously (β \u0026lt; 0.001, p = 0.024).\u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eStandardized effects of ACEs on CLD through social isolation, depression and frailty (\u003cem\u003eN\u003c/em\u003e = 17496)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"8\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eB\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e95%CI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eβ\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eSE\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eCR\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eACEs → Depression → CLD\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.006\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.004\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.008\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.009\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003e5.294\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eACEs \u003cb\u003e→\u003c/b\u003e Social isolation \u003cb\u003e→\u003c/b\u003e CLD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e− 0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.002\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.242\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.809\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eACEs → Depression → Frailty → CLD\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt; 0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt; 0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e3.881\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt; 0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eACEs \u003cb\u003e→\u003c/b\u003e Depression \u003cb\u003e→\u003c/b\u003e Social isolation \u003cb\u003e→\u003c/b\u003e CLD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.242\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.809\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eACEs → Social isolation → Frailty → CLD\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt; 0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt; 0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt; 0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt; 0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt; 0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e− 2.489\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e\u003cb\u003e0.013\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eACEs → Depression → Frailty → Social isolation → CLD\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt; 0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt; 0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt; 0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt; 0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt; 0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e− 2.256\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e\u003cb\u003e0.024\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eTotal Indirect\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e0.007\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e0.004\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0.009\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.011\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e5.052\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt; 0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eTotal Direct\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e0.015\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0.029\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.024\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.007\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e2.072\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e\u003cb\u003e0.038\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eTotal Effect\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e0.021\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e0.007\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0.035\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.034\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.007\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e3.017\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e\u003cb\u003e0.003\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"8\"\u003e\u003cem\u003eNote. CR\u003c/em\u003e, \u003cem\u003ecritical ratio\u003c/em\u003e; \u003cem\u003eSE\u003c/em\u003e, standard error; ACEs, Adverse childhood experience; CLD, chronic lung disease.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003ch2\u003eSensitivity analyses\u003c/h2\u003e\u003cp\u003eThree sensitivity analyses were conducted, and results are presented in Supplementary Table\u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003es1\u003c/span\u003e-6. Covariates were categorized into two distinct groups—demographic variables and health-related measures—and were incorporated separately into the analytical models. Mediation analyses were repeated after excluding participants with missing ACEs data. The results of these sensitivity analyses were consistent with the main findings, supporting the robustness of our conclusions.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe results indicated that ACEs were associated with CLDs, that mirrors previous research on the association between general ACEs and CLDs (Anda et al., 2008; Li et al., 2024). However, how ACEs affect CLDs remains unclear. According to the extant literature, the physiopathological mechanisms underlying the relationship between ACE and the aetiology of various chronic diseases likely involve organic responses to chronic psychosocial stress (Lopes et al., 2020). Exposure to traumatic stress during childhood can lead to lasting alterations in the central nervous system, including heightened activity of the hypothalamic\u0026ndash;pituitary\u0026ndash;adrenal (HPA) axis (Bremner, 2001). This may affect both lung development during childhood and adolescence and the functioning of the cardiorespiratory system across the lifespan (Anda et al., 2008). On the other hand, maternal exposure to a hostile environment and the resulting stress response may induce maternal system inflammation or fetal inflammation (Ji et al., 2021).\u003c/p\u003e\u003cp\u003eThe mediation analysis indicated that both depression and frailty served as mediators in the association between ACEs and CLDs. These observed mediating effects may operate through two potential mechanisms. One potential mechanism involves ACEs inducing persistent, long-term inflammatory responses in the body (Heard-Garris et al., 2020). Chronic inflammation can damage pulmonary tissues and impair the nervous system, potentially contributing to the development of depression, frailty, and, ultimately CLDs(Lee \u0026amp; Giuliani, 2019; Soysal et al., 2016). Another potential mechanism is that ACEs leave lasting psychological scars (Choi \u0026amp; Hwang, 2023), which may contribute to depression in adulthood. This condition can, in turn, lead to heightened feelings of stigma and shame, thereby reducing health-related quality of life (Suen et al., 2023). Frailty and poor psychological well-being are strongly correlated(Andrew et al., 2012). The accumulation of health deficits in older adults may create a self-perpetuating cycle of decline termed a\"frailty identity crisis\", in which perceived physical limitations reinforce psychological distress (Andrew et al., 2012).\u003c/p\u003e\u003cp\u003eThe findings also revealed that, while social isolation alone did not a direct effect on CLDs, it exerted a significant effect when combined with frailty. Social isolation by itself does not directly cause CLDs in older adults, which represents certain discrepancies with previous studies (Stoustrup et al., 2024). This discrepancy may stem from distinct sociocultural contexts. Specifically, the unique historical experiences of China's middle-aged and older adult, shaped by the One-Child Policy and economic hardships, has producted a generation with lower reliance on social welfare systems. However, when combined with frailty, social isolation produces a harmful synergy that significantly elevates the risk of CLDs. This interaction effect primarily occurs through limited access to healthcare services: frail individuals who are socially isolated face compounded barriers to medical care, preventive care, and necessary social support (Donovan \u0026amp; Blazer, 2020). Consequently, this dual burden of physical frailty and limited access to healthcare further exacerbates pulmonary vulnerability, resulting in greater susceptibility to respiratory infections and accelerated disease progression.\u003c/p\u003e\u003cp\u003eThe geospatial analysis revealed distinct regional patterns: ACEs exposure was markedly higher in southern provinces, whereas the prevalence of CLDs was more pronounced in central-western regions. This epidemiological distribution may be attributed to inadequate healthcare infrastructure combined with region-specific climatic factors, including persistent humidity in the south and arid, dust storm-prone conditions in the central-west. More importantly, lower familial socioeconomic status emerged as a key determinant, as indicated by substantially lower disease rates in the more economically developed southeastern provinces.\u003c/p\u003e\u003cp\u003eSeveral limitations of this study warrant discussion. First, the definition of CLDs in this study was based solely on participants\u0026rsquo; self-reported data, without corresponding medical diagnoses available in the CHARLS database. Second, data on threat-related ACEs relied on retrospective self-reporting, which may introduce recall bias.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe study confirms the significant relationship between ACEs and CLDs, as well as their mediation through depression, frailty, and social isolation using structural equation modeling, while also examining China-specific geographical patterns in ACEs distribution. These findings provide crucial evidence for implementing comprehensive CLDs prevention programs that adopt a life-course perspective and incorporate biopsychosocial elements.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCHARLS\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eChina Health and Retirement Longitudinal Study\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCLDs\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eChronic lung diseases\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eACEs\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eAdverse Childhood Experiences\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eFI\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003efrailty index\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCESD\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eThe Center for Epidemiologic Studies Depression Scale.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003eEthics approval and consent to participate\u003c/p\u003e\n\u003cp\u003eEthics approval for the study was granted by the Ethics Review Committee of Peking University, and all the participants provided signed informed consent at the time of participation. The study methodology was carried out in accordance with approved guidelines.\u003c/p\u003e\n\u003cp\u003eConsent for publication\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003eAvailability of data and materials\u003c/p\u003e\n\u003cp\u003eThe dataset collected and analyzed in the current study are available from the corresponding author on reasonable request\u003c/p\u003e\n\u003cp\u003eCompeting interests\u003c/p\u003e\n\u003cp\u003eThe authors declare that there are no conflicts of interest\u003c/p\u003e\n\u003cp\u003eFunding\u003c/p\u003e\n\u003cp\u003eThis research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\n\u003cp\u003eAuthors’ contributions\u003c/p\u003e\n\u003cp\u003eAll authors (Shuangwei Dong, Junpei Cai, and Xiaoning Zhang) have made substantial contributions to:\u003c/p\u003e\n\u003cp\u003eStudy conception/design and data interpretation\u003c/p\u003e\n\u003cp\u003eDrafting and critical revision of the manuscript\u003c/p\u003e\n\u003cp\u003eFinal approval of the submitted version\u003c/p\u003e\n\u003cp\u003eAcknowledgements\u003c/p\u003e\n\u003cp\u003eWe are grateful to the China Center for Economic Research at Beijing University for providing us with the data, and we thank the CHARLS research and field team for collecting the data.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAnda, R. F., Brown, D. W., Dube, S. R., Bremner, J. D., Felitti, V. J., \u0026amp; Giles, W. H. (2008). Adverse childhood experiences and chronic obstructive pulmonary disease in adults [Article]. \u003cem\u003eAmerican Journal of Preventive Medicine\u003c/em\u003e,\u003cem\u003e 34\u003c/em\u003e(5), 396-403. https://doi.org/10.1016/j.amepre.2008.02.002 \u003c/li\u003e\n\u003cli\u003eAndrew, M. K., Fisk, J. D., \u0026amp; Rockwood, K. (2012). Psychological well-being in relation to frailty: a frailty identity crisis? [Article]. \u003cem\u003eInternational Psychogeriatrics\u003c/em\u003e,\u003cem\u003e 24\u003c/em\u003e(8), 1347-1353. https://doi.org/10.1017/s1041610212000269 \u003c/li\u003e\n\u003cli\u003eBellis, M. A., Hughes, K., Ford, K., Rodriguez, G. R., Sethi, D., \u0026amp; Passmore, J. (2019). Life course health consequences and associated annual costs of adverse childhood experiences across Europe and North America: a systematic review and meta-analysis [Review]. \u003cem\u003eLancet Public Health\u003c/em\u003e,\u003cem\u003e 4\u003c/em\u003e(10), E517-E528. https://doi.org/10.1016/s2468-2667(19)30145-8 \u003c/li\u003e\n\u003cli\u003eBoey, K. B., KW). (1999). Cross-validation of a short form of the CES-D in Chinese elderly. \u003cem\u003eInternational Journal of Geriatric Psychiatry\u003c/em\u003e. \u003c/li\u003e\n\u003cli\u003eBremner, J. D. V., E. (2001). Stress and development: Behavioral and biological consequences. \u003cem\u003eDEVELOPMENT AND PSYCHOPATHOLOGY\u003c/em\u003e,\u003cem\u003e Vol.13\u003c/em\u003e. https://doi.org/10.1017/S0954579401003042 \u003c/li\u003e\n\u003cli\u003eChang, X. N., Jiang, X. Y., Mkandarwire, T., \u0026amp; Shen, M. (2019). Associations between adverse childhood experiences and health outcomes in adults aged 18-59 years [Article]. \u003cem\u003ePlos One\u003c/em\u003e,\u003cem\u003e 14\u003c/em\u003e(2), Article e0211850. https://doi.org/10.1371/journal.pone.0211850 \u003c/li\u003e\n\u003cli\u003eChen, L. H., Miocevic, M., \u0026amp; Falk, C. F. (2024). Tackling Challenges in Data Pooling: Missing Data Handling in Latent Variable Models with Continuous and Categorical Indicators [Article]. \u003cem\u003eStructural Equation Modeling-a Multidisciplinary Journal\u003c/em\u003e,\u003cem\u003e 31\u003c/em\u003e(4), 651-666. https://doi.org/10.1080/10705511.2023.2300079 \u003c/li\u003e\n\u003cli\u003eChen, Y. R. R., \u0026amp; Schulz, P. J. (2016). 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H., Kan, H. D., Lopez, A. D., Phillips, M. R., She, J., Vos, T., Wan, X., Xu, G. L., Yan, L. J. L., Yu, C. H., Zhao, Y., Zheng, Y. F., Zou, X. N., Naghavi, M., Wang, Y., Murray, C. J. L., Yang, G. H., \u0026amp; Liang, X. F. (2016). Cause-specific mortality for 240 causes in China during 1990-2013: a systematic subnational analysis for the Global Burden of Disease Study 2013 [Article]. \u003cem\u003eLancet\u003c/em\u003e,\u003cem\u003e 387\u003c/em\u003e(10015), 251-272. https://doi.org/10.1016/s0140-6736(15)00551-6 \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Adverse childhood experiences, Chronic lung diseases, Mediating effect","lastPublishedDoi":"10.21203/rs.3.rs-7514546/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7514546/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjectives\u003c/h2\u003e\u003cp\u003eThis study examined the association from Chronic lung diseases (CLDs) to Adverse childhood experiences (ACEs) with a specific focus on examining the potential mediating effects of depression, frailty, and social isolation.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eData for this retrospective cohort study were obtained from participants enrolled in the China Health and Retirement Longitudinal Study (CHARLS). This study estimated competing structural equation model (SEM) examining the associations from ACEs to CLDs, and the mediating roles of depressive, frailty and social isolation.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eThis study found ACEs had significant direct (\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.024, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and total (\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.034, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.003) effects on CLDs. ACEs had a significant indirect effect on CLDs through depression (β\u0026thinsp;=\u0026thinsp;0.009, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), through Isolation (β\u0026thinsp;=\u0026thinsp;0.003, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.809). ACEs exerted multi-step indirect effects on CLDs through various pathways. ACEs influenced CLDs indirectly through both Depression and Frailty (β\u0026thinsp;\u0026lt;\u0026thinsp;0.001, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), through Depression and Isolation (β\u0026thinsp;\u0026lt;\u0026thinsp;0.001, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.809), through Isolation and Frailty (β\u0026thinsp;\u0026lt;\u0026thinsp;0.001, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.013). ACEs had a multi-step indirect effect on CLDs through Depression, Frailty, and Isolation (β\u0026thinsp;\u0026lt;\u0026thinsp;0.001, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.024).\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eThis study establishes a significant association between ACEs and CLDs, in the elderly population. Furthermore, depression, frailty and social isolation as three mediating factors in the ACEs and CLDs relationship.\u003c/p\u003e","manuscriptTitle":"Linking Adverse Childhood Experiences and Chronic Lung Diseases: The Mediating Role of Depression, Frailty, and Social Isolation","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-23 06:49:28","doi":"10.21203/rs.3.rs-7514546/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2025-12-16T02:52:24+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"273340912210917995634453554345777925294","date":"2025-12-04T15:39:06+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"273785391182633923964538643038316134822","date":"2025-12-04T15:22:43+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-09-13T11:00:55+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-13T10:56:08+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-09-08T09:38:57+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-09-06T02:29:01+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Public Health","date":"2025-09-06T02:24:34+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"9dcf8081-175c-4b8d-a87b-e869aed7ea76","owner":[],"postedDate":"September 23rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-09-23T06:49:28+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-23 06:49:28","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7514546","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7514546","identity":"rs-7514546","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}