The Moderating Role of Adverse Childhood Experiences in the Relationship Between Disability and Depression in Old Age: Evidence From China
Article information
Abstract
Objective
To investigate the association between adverse childhood experiences (ACEs) and depression in old age, and further examine the moderating role of ACEs on the relationship between later-life disability and depression.
Methods
This study utilizes data from the 2018 China Health and Retirement Longitudinal Study and the 2014 life course survey, employing the binary logistic regression to explore the relationship between ACEs and depression in old age, and applying a multiplicative interaction analysis method to explore the moderating effect of ACEs on the relationship between later-life disability and depression.
Results
The results show a positive association between ACEs and the likelihood of depression in old age (moderate relationship with parents: odds ratio [OR]=1.140, 95% confidence interval [CI] [1.006–1.293]; poor relationship with parents: OR=1.438, 95% CI [1.229– 1.684]; experiencing family stress events: OR=1.214, 95% CI [1.077–1.369]; living in an unsafe community: OR=1.284, 95% CI [1.049– 1.571]; sometimes or often being bullied by peers: OR=1.415, 95% CI [1.188–1.685]). Additionally, the association between later-life disability and depression is significantly weaker among older adults who reported sometimes or often being bullied by peers during childhood, compared to those without such experiences (OR=0.410, 95% CI [0.204–0.826]).
Conclusion
ACEs are positively associated with the likelihood of depression in old age, yet they may also serve a protective role in mental health during later-life severe adversity, such as disability. This protective effect may be attributed to post-traumatic psychological resilience, highlighting the importance of targeted interventions to enhance resilience in individuals exposed to trauma, as well as the integration of trauma-informed care into mental health services for older adults.
INTRODUCTION
Mental health issues represent a significant global health challenge. The WHO emphasizes the “urgent need to transform the state of mental health and mental health care,” integrating mental health into universal health coverage plans and sustainable development goals [1]. Depression, a common mental disorder, affects approximately 5% of adults worldwide. In 2019, depression accounted for approximately 47 million years lived with disability (YLDs), making it the second leading cause of non-fatal health loss [2]. Additionally, the most common mental health conditions for older adults are depression and anxiety. With the global population aging, depression has garnered increasing attention [3]. From 1990 to 2019, YLDs due to depression among the elderly aged 70 years and above increased by approximately 1.3 times globally, while in China, it increased by about 2.5 times [4], nearly twice the global average growth rate. The current rapid aging trend in China suggests a significant disease burden challenge due to depression among older adults. Depression prevention and control have become key targets in China’s mental health promotion action plan, as outlined in the “Healthy China Action (2019–2030).” [5]
The etiology of depression in the elderly is complex, influenced by physical conditions, social environments, and cumulative factors throughout the life course, such as early life experiences, and the gradual loss of living intrinsic functional levels [3]. Existing research generally agrees that the incidence of depression is significantly higher among older adults with activities of daily living impairments due to functional limitations and social isolation [6,7]. Regarding the relationship between adverse childhood experiences (ACEs) and depression in old age, most studies reveal a positive correlation [8,9]. The concept of ACEs was formalized in a landmark epidemiological study conducted in 1995 by the Centers for Disease Control and the Kaiser Permanente healthcare organization in California [10,11]. In that study, ACEs referred to three specific kinds of adversity children faced in the home environment—various forms of physical and emotional abuse, neglect, and household dysfunction (such as substance abuse in a family member, mental health problems, divorce, a member’s incarceration, etc.) [10]. Initially, the ACEs study focused on adversities within the home, but subsequent research has expanded to include adversities in the community and among peers. These experiences were recognized for their long-term impact on individuals, including increased risks of physical and mental health problems and social issues, dramatically increasing risks of heart disease, diabetes, obesity, depression, substance abuse, smoking, poor academic achievement, time out of work, and early death [10]. However, some opposing views in psychology, such as posttraumatic growth [12] and resilience theory [13], suggest that ACEs may, in some cases, enhance individual psychological resilience, resulting in “adversity immunity” or “depression resistance” effects. This highlights the complex relationship between ACEs and depression in old age. Based on this, this study aims to explore this relationship and further analyze the moderating effect of ACEs on the relationship between disability and depression in old age, hoping to supplement some evidence from China regarding the mechanisms such as posttraumatic growth and psychological resilience that may exist in the impact of the ACEs on mental health in old age.
METHODS
Data source
The data used in this study was obtained from the 2014 and 2018 China Health and Retirement Longitudinal Study (CHARLS).
CHARLS is a large-scale national follow-up survey designed and implemented by the Social Science Research Center of Peking University for middle-aged and older adults (45 years old and above). CHARLS conducted its national baseline survey in 2011, covering 150 county-level units and 450 village-level units across 28 provinces (autonomous regions and municipalities), with approximately 17,000 individuals from 10,000 households. Follow-up surveys were conducted in 2013, 2015, 2018, and 2020. By 2020, the sample covered 19,000 respondents [14]. Additionally, a life course survey was conducted retrospectively in 2014. CHARLS adopted a multi-stage sampling method with probability proportional to scale. The respondents were interviewed face-to-face in their homes via computer-assisted personal interviewing technology [15]. CHARLS data can be accessed through its official website (http://charls.pku.edu.cn/). The CHARLS study received approval from the Biomedical Ethics Review Committee of Peking University (IRB00001052-11015). Each participant provided written informed consent, and all procedures were conducted according to relevant guidelines and regulations [16]. The 2018 survey covered domains such as household conditions, health status and functioning, cognition and depression, healthcare and insurance, and socioeconomic status. The 2014 life course survey collected data on major areas of individual life histories, such as growth, education, marriage, childbirth, and employment, providing information on ACEs for this study [17].
This study used the 2018 dataset, matching with the 2014 data using personal ID, and included older adults aged 60 years and above, totaling 8,657 samples. The detailed procedures for sample selection are as follows (Figure 1).
Flowchart illustrating the process of sample screening.
Measurements
This study aims to investigate the association between ACEs and the incidence of depressive disorders in old age (60 years and above) and further analyze the moderating effect of ACEs on the relationship between later-life disability and depression. Among the variables used in this study, apart from the current household assets as a numerical variable, all other variables are categorical.
In this study, the dependent variable is “whether one has depression,” measured using the Center for Epidemiological Studies Depression Scale Revised (CESD-R-10). This scale is a self-report measure of depression, with the total score calculated by summing 10 items. Samples with more than two missing items were excluded. Any score equal to or above 10 is considered indicative of depression [18]. The CESD is primarily used in epidemiological research to identify individuals who may have depressive symptoms, rather than as a clinical diagnostic tool.
The core explanatory variable in this study is “whether one has had ACEs,” which includes three dimensions: early family environment, early peer relationships, and early community environment. The variables measuring the early family environment include: 1) “whether one experienced stressful family events or environments in early life,” including the death or divorce of biological parents before age 18, long-term parental illness, severe mental illness or physical disability in parents, and adverse behaviors of parents such as alcoholism, smoking, gambling, drug abuse, unstable employment, lying, frequent fights, involvement in criminal activities, arrest or imprisonment and 2) “relationship with parents,” represented by the combined scores of the relationship with the father and the relationship with the mother, divided into tertiles. The variable measuring the early peer relationships is the frequency of bullying by neighboring children, referred to as peer bullying frequency. The variable measuring early community environment is the perceived safety of the community.
Based on the model of social determinants of health and existing research findings, control variables in this study include socio-demographic characteristics [19,20], socioeconomic status [20], medical insurance [21], lifestyle, and health status [20,22,23]. Socio-demographic variables include gender, age, and marital status. Age is divided into three stages: 60–69 years as younger elderly, 70–79 years as middle-aged elderly, and 80 years and above as older elderly. Marital status is categorized into two groups: those who are separated or have no spouse, and those who are married and not separated. Socioeconomic status is measured by current household assets, including cash, electronic money, deposits in financial institutions, bonds, stocks, funds, assets in others’ names but owned by the respondents, housing provident funds, unreturned capital, unpaid wages, and other debts owed by others. The total value of household assets was calculated by summing these values, with specific amounts used if provided, or average values for ranges. Anomalous values were processed. Medical insurance is measured by whether the respondent holds medical insurance, including urban employee insurance, urban and rural resident insurance, public medical care, medical assistance, commercial insurance, major illness insurance for urban unemployed residents, long-term care insurance, and supplementary insurance, with holding any of these considered as having insurance. Lifestyle variables include current social activities [24], at least 10 minutes of exercise per week [25], and current smoking or drinking status [20]. The Physical Self-Maintenance Scale (PSMS) is commonly used to assess disability status [26]. A disability is any condition of the body or mind (impairment) that makes it more difficult for the person with the condition to do certain activities (activity limitation) and interact with the world around them (participation restrictions) [27]. According to the Americans with Disabilities Act (ADA), a person is considered to have a disability if they have a physical or mental impairment that substantially limits one or more major life activities [28]. PSMS includes six items: dressing, bathing, eating, getting in and out of bed, using the toilet, and controlling bladder and bowel functions. Each item is rated on a four-level scale: no difficulty, some difficulty but can still complete, difficulty requiring assistance, and unable to complete. If any item is rated as requiring assistance or unable to complete, the individual is classified as disabled [29]. The basic characteristics of the main variables for the depression and non-depression groups are shown in Supplementary Table 1.
Statistical analysis
The association analysis was conducted using logistic regression models. In the section on moderating effect analysis, this study first illustrates the results graphically to preliminarily explore the possible differences between groups, employing binary logistic regression to report the marginal effects of each interaction group and holding all variables except the main variables and interaction terms at their mean values. Secondly, a multiplicative interaction effect method based on logistic regression models was employed to rigorously calculate and analyze the moderating effect of ACEs on the relationship between later-life disability and depression. The calculation for the multiplicative interaction effect is as follows:
Taking the interaction between disability status and the relationship with parents as an example, the multiplicative interaction effect is interpreted as the ratio of the odds ratio (ORab) of depression among the disabled elderly with poor parental relationships (using the non-disabled counterparts as the reference group) to the odds ratio (ORcd) of depression among the disabled elderly with good parental relationships (also using the non-disabled group as the reference):
This ratio reflects whether the impact of disability on depression differs depending on the quality of early-life parent-child relationship, i.e., whether a significant moderation effect of early-life parent-child relationship exists on the relationship between disability status and depression in later life. An illustration of the multiplicative interaction effect method is shown in Figure 2 (data are hypothetical). Stata 18.0 (Stata Corp.) was used to conduct the above statistical analyses, with a significance level set at 0.05.
Illustration of the multiplicative interaction effect method. OR, odds ratio.
RESULTS
The prevalence of depression among older adults
Among older adults aged 60 years and above, the proportion of those with depressive disorders (41.69%) is lower than that of those without depressive disorders (58.31%). Older adults who had experienced stressful family events (42.95%), reported poor parental relationships (47.51%), were sometimes or often subjected to peer bullying (49.50%), or had lived in less safe community environments (52.62%) during childhood demonstrated a higher prevalence of depression in later life. Conversely, those who had not experienced stressful family events (38.07%), reported good or moderate parental relationships (38.89% and 42.95%), had never or rarely been bullied by peers (40.50%), or had lived in safe communities (40.36%) during childhood exhibited a lower prevalence of depression in later life (Table 1).
Prevalence of depression among older adults with different adverse childhood experiences status
The relationship between ACEs and depression in old age
Further regression analysis reveals that, after adjusting for individuals’ sociodemographic characteristics, socioeconomic status, lifestyle behaviors, and health conditions (including gender, age, marital status, household assets, medical insurance coverage, social activity participation, physical exercise, smoking and drinking behaviors, and disability status), compared to older adults who had good relationships with their parents during childhood, those with moderate or poor relationships had 14.0% and 43.8% higher odds of developing depression, respectively. Compared to older adults who had not experienced stressful family events during childhood, those who had experienced such events had 21.4% higher odds of developing depression. Compared to older adults who lived in relatively safe communities during childhood, those who lived in less safe communities had 28.4% higher odds of developing depression. Compared to older adults who were never or rarely bullied by peers during childhood, those who were sometimes or often bullied had 41.5% higher odds of developing depression. These regression results suggest a positive association between ACEs and depression in old age (Table 2).
Relationship between adverse childhood experiences and depression among older adults
The moderating effect of ACEs on the relationship between later-life disability and depression
Existing research suggests that disability is a risk factor for depression among older adults [6,7], and the likelihood of depression increases with the severity of disability [30]. Previous data analysis in this study indicated a positive correlation between ACEs and depression in old age. Furthermore, after disaggregating older adults by disability status, this study finds that, among those with disability, older adults who had experienced stressful family events or lived in less safe communities in childhood show a greater difference in the proportion of individuals with depression compared to those without depression (40.92% and 67.74%) than those who had not experienced these ACEs (31.50% and 36.38%). However, among those with disability, older adults who had a poor relationship with their parents or who had been sometimes or often bullied by peers in childhood show a smaller difference in the proportion of individuals with depression compared to those without depression (39.02% and 26.82%) than those who had not experienced these ACEs (40.06% and 41.14%) (Table 3). This suggests that ACEs, particularly peer bullying, may exert a potential moderating effect on the association between later-life disability and the likelihood of depression.
Prevalence of depression among older adults with different disability status and adverse childhood experiences
To further examine the significance of the moderating effect of ACEs, this study first presents the results graphically to explore the potential differences between groups. Figure 3 illustrates the marginal effects of disability on depression among older adults with varying ACEs. Across all ACEs groups, the marginal effect of disability on depression (solid line) is greater compared to non-disability (dashed line). However, the marginal effects of disability on depression appear relatively smaller among older adults who experienced stressful family events, were sometimes or often bullied by peers, or had moderate to poor relationships with their parents during childhood, compared to those without such ACEs. In addition, a multiplicative interaction effect method based on logistic regression models was employed to rigorously assess the moderating role of ACEs in the relationship between later-life disability and depression. The results show that the association between disability and depression is significantly weaker among older adults who were sometimes or often bullied by peers during childhood than among those who were never or rarely bullied (OR=0.410; 95% confidence interval, 0.204–0.826), suggesting that ACEs significantly moderate the relationship between disability and depression in old age (Table 4).
Marginal effects of disability on depression among older adults with different adverse childhood experiences. A: Living in communities with different safety levels. B: With different relationships with parents. C: With different experiences of family stressful events. D: With different frequencies of peer bullying.
Differential effects of disability among older adults with different adverse childhood experiences
DISCUSSION
This study provides supplementary evidence from China for the moderating effect of ACEs on the relationship between disability and depression in old age. It finds that ACEs—including poor relationships with parents, exposure to family stress events, living in unsafe communities, and experiencing peer bullying (sometimes or often)—are positively associated with the likelihood of developing depressive disorders in later life. Moreover, the study reveals a potential moderating effect of ACEs on the relationship between disability and depression in old age, as suggested by the finding that the impact of disability on depression is significantly lower among older adults who experienced sometimes or often peer bullying during childhood, compared to those who did not.
The positive association between ACEs and depression in later life has been confirmed by numerous studies. ACEs exert significant impacts on children’s neurological, behavioral, and psychological development, leading to long-lasting effects in broader domains [31]. Neuroscientific research has shown that early life experiences affect the development of the prefrontal cortex, hippocampus, hypothalamus, and amygdala, as well as communication among these regions, increasing vulnerability to mental and physical health disorders in later life [32]. However, existing studies have predominantly focused on the direct negative relationship between ACEs and later-life mental health, while overlooking the possibility that ACEs may also play a protective role in later-life mental health by fostering psychological resilience [32] and other adaptive mechanisms.
Resilience is the ability to adapt in the face of trauma, adversity, tragedy or even significant ongoing stressors [33]. Psychological resilience theory posits that adverse experiences can prompt individuals to draw on both internal and external resources to cope with hardship, thereby fostering the development of more effective coping mechanisms, such as stronger adversity-coping abilities, closer interpersonal relationships, and a deeper understanding of life’s meaning. This adaptive process not only enables individuals to navigate adversity successfully but also helps to strengthen and enhance their capacity to deal with future challenges, ultimately leading to the development of psychological resilience [12,34-36]. Although adversity can act as a catalyst for developing psychological resilience, the catalytic effect is influenced by various factors, including individual personality traits, individual coping strategies, social support and the nature of the adverse experience [37,38]. A study on the relationship between adversity cognition and psychological resilience among rural college students showed that the impact of left-behind experiences on psychological resilience is moderated by negative cognition. If rural college students who experienced being left behind during childhood have fewer negative cognitions about adversity, their psychological resilience decreases less. Conversely, if they have more negative cognitions about adversity, their psychological resilience declines to a greater extent [36]. Nonetheless, psychological resilience remains a relatively common trajectory of psychological response to adversity [39]. Existing research has repeatedly identified four response trajectories to stressful events: chronic symptoms, recovery, delayed symptoms, and psychological resilience [40]. On average, two-thirds of survey participants in 63 trajectory analysis studies exhibited psychological resilience following adversity [40,41].
Psychological resilience exerts a certain protective effect on health. The ability to cope well with, and adapt to, challenging life circumstances and events in older age is linked to a lower risk of death, suggests a large nationally representative study [42]. Self-efficacy is an important component of psychological resilience and is explicitly identified as a key dimension for measuring resilience in the Connor-Davidson Resilience Scale (CD-RISC). A study on the relationship between early-life adversity and later-life mental health indicated that self-efficacy significantly mediated the relationship between early-life adversity and mental health, as well as satisfaction with life [43]. While psychological resilience is a common response to adversity, numerous studies have confirmed the negative association between ACEs and mental health in old age [39,44]. Combining these conclusions, this study suggests that although the psychological resilience mechanism may not directly reverse the negative impact of ACEs on mental health in old age, it may exert some protective effect on mental health [36].
This article also has some limitations. Firstly, apart from ACEs, other data are mostly cross-sectional, which can only yield associative conclusions. In the future, it will be necessary to further distinguish the temporal order of variables to analyze causal relationships. Secondly, the stressful family events defined in this study include options such as parental divorce, death, alcoholism, and smoking, which are subjectively considered to have different levels of impact. However, robustness analysis conducted after excluding alcoholism and smoking options yielded consistent results. Thirdly, this study relies on retrospective self-reports of childhood adversity, which may be subject to recall bias. Participants may misremember early life experiences, potentially leading to measurement error and biased estimates of the relationship between ACEs and depression. Finally, this study has controlled for most dimensions identified in existing research. However, due to limitations in the available datasets, certain variables—such as perceived emotional support—could not be included as controls.
In conclusion, this study investigates the relationship between ACEs and depression in old age, and further examines the moderating role of ACEs on the relationship between later-life disability and depression. The findings show that ACEs are positively associated with the likelihood of developing depressive disorders in old age, yet they may also play a protective role in mental health during severe adversity during later life. This protective effect may stem from the psychological resilience, highlighting that the targeted interventions to enhance psychological resilience—such as community-based support programs, professional counseling services, and adaptive coping skills training—should be promoted. Additionally, it is recommended that trauma-informed care be systematically integrated into elderly mental health services.
Supplementary Materials
The Supplement is available with this article at https://doi.org/10.30773/pi.2024.0380.
Details of variables that characterize depressed and non-depressed group
Notes
Availability of Data and Material
CHARLS data can be accessed through its official website (http://charls.pku.edu.cn/).
Conflicts of Interest
The authors have no potential conflicts of interest to disclose.
Author Contributions
Conceptualizing: Yiran Wang, Lu Tan. Data curation: Yiran Wang, Lu Tan. Formal analysis: Yiran Wang, Lu Tan. Supervision: Wannian Liang. Writing—original draft: Yiran Wang, Lu Tan. Critical revision: Xiaoqian Yan, Hanyi Xu. Writing—review & editing: Xiaoqian Yan, Hanyi Xu.
Funding Statement
This work was supported by Shui Mu Tsinghua Scholar Program, and General Program of China Postdoctoral Science Foundation (grant number: 2024M751590). The sponsors played no part in the study design, data collection, analysis, interpretation, manuscript writing, or study approval.
Acknowledgments
None