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The Change of Depression Network Structure and Core Symptoms Across the Lifespan: Evidence from Large-Scale Data
Xin Guogang, Li Pengyang, Chen Qinian, Jiang Ling, Li Qing, Luo Peiyu, Wang Xiaohua
Journal of Psychological Science ›› 2026, Vol. 49 ›› Issue (2) : 303-314.
PDF(1255 KB)
PDF(1255 KB)
The Change of Depression Network Structure and Core Symptoms Across the Lifespan: Evidence from Large-Scale Data
Depression is one of the most prevalent and disabling mental health disorders worldwide. While extensive research has examined the epidemiology and risk factors of depression, less is known about how the network structure and core symptoms of depression evolve across the lifespan. According to the network theory of mental disorders, depression is conceptualized as a network of interconnected symptoms, with some symptoms playing a central role in maintaining the disorder. However, it remains unclear whether these core symptoms remain stable or shift across different developmental stages. Using large-scale data from the China Family Panel Studies (CFPS), this study employs network analysis to examine the structural variations and symptom centrality of depression across different age groups, providing empirical evidence on the dynamic changes in depressive symptomatology over the lifespan.
A total of 34,668 participants aged 10 to 99 years were included in the study. Depressive symptoms were assessed using the Chinese version of the Center for Epidemiologic Studies Depression Scale. The data were analyzed in SPSS 24.0 and R 4.0.4. Network structures were estimated for 16 different age groups. The network comparison test and global strength analysis were conducted to identify variations in depressive symptom networks across these groups.
The results revealed several critical findings. First, of the 121 network comparisons, 46 showed significant differences, suggesting that depressive symptom networks undergo substantial changes throughout the lifespan. Second, the global strength of depressive symptom networks increased with age, reaching its peak at 50~54 years before gradually declining in older age groups. This pattern indicates that midlife may represent a critical period of heightened vulnerability to depression due to accumulated stressors from career demands, family responsibilities, and social role transitions. Third, while “depressed mood”, “sadness”, and “loneliness” consistently ranked as highly central symptoms across all age groups, distinct core symptoms emerged at different developmental stages. During early adolescence (ages 10~12 years), "fearful" and "unhаpру" were the most central symptoms, reflecting the psychological challenges of academic stress and social comparison. In middle adolescence (ages 13~15 years), "people dislike" became a dominant symptom, aligning with increased sensitivity to peer relationships. For individuals in the transitional stages of middle adulthood and old age (ages 55-64 years), "unhаpру" emerged as a primary symptom, likely due to occupational burnout and financial pressures. In late adulthood (65-74 years), "get going" became the central symptom, consistent with age-related physical decline and decreased social engagement. Finally, among the oldest adults (aged 75 and older), "crying" emerged as a key symptom, possibly indicating increased emotional vulnerability.
These findings have significant implications for targeted interventions across the lifespan. Given the dynamic nature of depressive symptom networks, age-specific treatment strategies should be implemented. Early interventions for adolescents should focus on reducing social isolation, while workplace mental health programs may be essential for middle-aged individuals facing occupational stress. In contrast, interventions for older adults should prioritize enhancing social participation and addressing physical health challenges to prevent motivation loss and emotional distress. Moreover, network analysis demonstrated that as individuals age, depressive symptoms become more interconnected, contributing to an increase in global network strength. The peak in midlife suggests that individuals in this age group may be at the highest risk of persistent depression due to the cumulative burden of life stressors. However, the subsequent decline in network strength among older adults suggests that aging-related protective factors, such as social support, may help mitigate depressive symptom severity. This study advances our understanding of depression heterogeneity by systematically examining how symptom networks evolve across the lifespan. The findings highlight the importance of adopting a developmental perspective in depression research and clinical practice. Future studies should adopt longitudinal designs to examine how core symptoms evolve within individuals and how the overall network structure fluctuates in response to life transitions, ultimately informing more personalized and effective mental health interventions.
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We hypothesized that depressive symptoms not meeting full standard criteria for Major Depression would be associated with significant functional impairment among older adults over the course of a 13-year follow-up interval. Specifically, we developed criteria for a form of depression whose core symptoms did not include sadness or dysphoria.Population-based 13-year follow-up survey.Community-dwelling adults living in East Baltimore in 1981.Subjects were the 1612 participants of the Baltimore sample of the Epidemiologic Catchment Area Program aged 50 years and older at the initial interview in 1981.The subjects were sorted into four categories based on their responses at baseline: (1) persons meeting standard criteria for Major Depression; (2) persons meeting alternative criteria for depression with dysphoria or (3) without dysphoria; and (4) a comparison category of persons not meeting any criteria for depression ("noncases"). The mortality and functional status of each group were compared after a 13-year follow-up interval.Compared with non-cases, participants aged 50 years and older who reported depressive symptoms but who denied sadness or dysphoria (nondysphoric depression) were at increased risk for death (relative risk (RR) = 1.70; 95% confidence interval (CI) (1.09, 2.67)), impairment in activities of daily living (RR = 3.76; 95% CI (1.73, 8.14)), impairment in instrumental activities of daily living (RR = 5.07; 95% CI (2.24, 11.44)), psychologic distress (RR = 3.68; 95% CI (1.47, 9.21)), and cognitive impairment (RR = 3.00; 95% CI (1.31, 6.89)) after a 13-year follow-up interval. The findings were not wholly explained by potentially influential baseline characteristics such as age, education, selected comorbid medical conditions, and functional status.Among adults aged 50 years and older, nondysphoric depression may be as important as Major Depression in relation to the development of functional disability and other long-term outcomes.
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Onset of depressive symptoms after the age of 65, or late-life depression (LLD), is common and poses a significant burden on affected individuals, caretakers, and society. Evidence suggests a unique biological basis for LLD, but current hypotheses do not account for its pathophysiological complexity. Here we propose a novel etiological framework for LLD, the age-by-disease biological interaction hypothesis, based on the observations that the subset of genes that undergoes lifelong progressive changes in expression is restricted to a specific set of biological processes, and that a disproportionate number of these age-dependent genes have been previously and similarly implicated in neurodegenerative and neuropsychiatric disorders, including depression. The age-by-disease biological interaction hypothesis posits that age-dependent biological processes (i) are "pushed" in LLD-promoting directions by changes in gene expression naturally occurring during brain aging, which (ii) directly contribute to pathophysiological mechanisms of LLD, and (iii) that individual variability in rates of age-dependent changes determines risk or resiliency to develop age-related disorders, including LLD. We review observations supporting this hypothesis, including consistent and specific age-dependent changes in brain gene expression and their overlap with neuropsychiatric and neurodegenerative disease pathways. We then review preliminary reports supporting the genetic component of this hypothesis. Other potential biological mediators of age-dependent gene changes are proposed. We speculate that studies examining the relative contribution of these mechanisms to age-dependent changes and related disease mechanisms will not only provide critical information on the biology of normal aging of the human brain, but will inform our understanding of age-dependent diseases, in time fostering the development of new interventions for prevention and treatment of age-dependent diseases, including LLD.
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In this study, the difference of depression network structures between the widowed and non-widowed older people and the associations of family capital, neighborhood cohesion, and neighborhood built environment with depressive symptoms were explored by using network analysis.This study fitted network models to two subsamples extracted from a nationally representative and cross-sectional data from China Family Panel Studies (CFPS). Depressive symptom levels and the effect of the three possible influencing factors related on depression were compared.The network structures of depression across the widowed and the non-widowed older people were different to some extent but significantly associated with one another. Neighborhood cohesion were significantly related to severe depressive symptoms in both subsamples. Neighborhood built environment mattered for the non-widowed older people, but not for their counterparts. Family capital also functioned in a different way for the two subsamples.Investigation was carried out using cross-sectional data, and changes in contents could alter the network structure. In addition, grief-related variables were not included. New studies replicating the current findings with a wider range of contents, multiple time points and a larger sample are warranted.This study added evidence to a growing body of literature on depressive symptom patterns for the widowed older people and their counterparts. Tailored service and treatment could be developed for the widowed and non-widowed older people based on their features of depression. The contextual factors including family, neighborhood, and physical environment could be taken into account when considering their association with depressive symptoms.Copyright © 2020. Published by Elsevier B.V.
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The present study used meta-analytic techniques (number of samples = 92) to determine the patterns of mean-level change in personality traits across the life course. Results showed that people increase in measures of social dominance (a facet of extraversion), conscientiousness, and emotional stability, especially in young adulthood (age 20 to 40). In contrast, people increase on measures of social vitality (a 2nd facet of extraversion) and openness in adolescence but then decrease in both of these domains in old age. Agreeableness changed only in old age. Of the 6 trait categories, 4 demonstrated significant change in middle and old age. Gender and attrition had minimal effects on change, whereas longer studies and studies based on younger cohorts showed greater change.
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The network approach to psychopathology conceptualizes mental disorders as networks of mutually reinforcing nodes (i.e., symptoms). Researchers adopting this approach have suggested that network topology can be used to identify influential nodes, with nodes central to the network having the greatest influence on the development and maintenance of the disorder. However, because commonly used centrality indices do not distinguish between positive and negative edges, they may not adequately assess the nature and strength of a node's influence within the network. To address this limitation, we developed 2 indices of a node's expected influence (EI) that account for the presence of negative edges. To evaluate centrality and EI indices, we simulated single-node interventions on randomly generated networks. In networks with exclusively positive edges, centrality and EI were both strongly associated with observed node influence. In networks with negative edges, EI was more strongly associated with observed influence than was centrality. We then used data from a longitudinal study of bereavement to examine the association between (a) a node's centrality and EI in the complicated grief (CG) network and (b) the strength of association between change in that node and change in the remainder of the CG network from 6- to 18-months postloss. Centrality and EI were both correlated with the strength of the association between node change and network change. Together, these findings suggest high-EI nodes, such as emotional pain and feelings of emptiness, may be especially important to the etiology and treatment of CG. (PsycINFO Database Record(c) 2016 APA, all rights reserved).
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Based on emerging evidence, mood disorders can be plausibly conceptualized as networks of causally interacting symptoms, rather than as latent variables of which symptoms are passive indicators. In an innovative approach in nursing research, we used network analysis to estimate the network structure of 20 perinatal depressive (PND) symptoms. Then, two proof-of-principle analyses are presented: Incorporating stress and reproductive biomarkers into the network, and comparing the network structure of PND symptoms between non-depressed and depressed women. We analyzed data from a cross-sectional sample of 515 Latina women at the second trimester of pregnancy and estimated networks using regularized partial correlation network models. The main analysis yielded five strong symptom-to-symptom associations (e.g., cry-sadness), and five symptoms of potential clinical importance (i.e., high centrality) in the network. In exploring the relationship of PND symptoms to stress and reproductive biomarkers (proof-of-principle analysis 1), a few weak relationships were found. In a comparison of non-depressed and depressed women's networks (proof-of-principle analysis 2), depressed participants had a more connected network of symptoms overall, but the networks did not differ in types of relationships (the network structures). We hope this first report of PND symptoms as a network of interacting symptoms will encourage future network studies in the realm of PND research, including investigations of symptom-to-biomarker mechanisms and interactions related to PND. Future directions and challenges are discussed. © 2017 Wiley Periodicals, Inc.© 2017 Wiley Periodicals, Inc.
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The heterogeneous aetiology of major depressive disorder (MDD) might affect the presentation of depressive symptoms across the lifespan. We examined to what extent a range of mood, cognitive, and somatic/vegetative depressive symptoms were differentially present depending on patient's age.Data came from 1404 participants with current MDD (aged 18-88 years) from two cohort studies: the Netherlands Study of Depression and Anxiety (NESDA) and the Netherlands Study of Depression in Older Persons (NESDO). Associations between age (per 10 years) and 30 depressive symptoms as well as three symptom clusters (mood, cognitive, somatic/vegetative) were assessed using logistic and linear regression analyses.Depression severity was found to be stable with increasing age. Nevertheless, 20 (67%) out of 30 symptoms were associated with age. Most clearly, with ageing there was more often early morning awakening [odds ratio (OR) 1.47, 95% confidence interval (CI) 1.36-1.60], reduced interest in sex (OR 1.42, 95% CI 1.31-1.53), and problems sleeping during the night (OR 1.33, 95% CI 1.24-1.43), whereas symptoms most strongly associated with younger age were interpersonal sensitivity (OR 0.72, 95% CI 0.66-0.79), feeling irritable (OR 0.73, 95% CI 0.67-0.79), and sleeping too much (OR 0.75, 95% CI 0.68-0.83). The sum score of somatic/vegetative symptoms was associated with older age (B = 0.23, p < 0.001), whereas the mood and cognitive sum scores were associated with younger age (B = -0.20, p < 0.001; B = -0.04, p = 0.004).Depression severity was found to be stable across the lifespan, yet depressive symptoms tend to shift with age from being predominantly mood-related to being more somatic/vegetative. Due to the increasing somatic presentation of depression with age, diagnoses may be missed.
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Common folklore seems to suggest that adolescents are particularly susceptible to peer influence. However, from the literature the exact age differences in susceptibility to peer influence remain unclear. The current study's main focus was to chart the development of general susceptibility to peer pressure in a community sample of 10-18 year olds (N =464) with the recently developed Resistance to Peer Influence Scale (RPI). The one-factor structure of the RPI was cross-validated in the present sample, and the RPI was equally reliable at all ages. As expected, general resistance to peer influence increased during adolescence. In addition, gender differences were most pronounced during mid-adolescence, when girls were more resistant to peer influence than boys. These findings are explained in terms of psychosocial maturation during adolescence.
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Long-term longitudinal studies are needed to delineate the trajectory of depressive symptoms across adulthood and to individuate factors that may contribute to increases in depressive symptoms in older adulthood.To estimate the trajectory of depressive symptoms across the adult life span; to test whether this trajectory varies by demographic factors (sex, ethnicity, and educational level) and antidepressant medication use; and to test whether disease burden, functional limitations, and proximity to death explain the increase in depressive symptoms in old age.Longitudinal study.Community.The study included 2320 participants (47.0% female; mean [SD] age at baseline, 58.1 [17.0] years; range, 19-95 years) from the Baltimore Longitudinal Study of Aging.Estimated trajectory of depressive symptoms modeled from 10, 982 assessments (mean [SD] assessments per participant, 4.7 [3.6]; range, 1-21) based on the Center for Epidemiologic Studies Depression scale and 3 subscales (depressed affect, somatic complaints, and interpersonal problems).The linear (γ10 = 0.52; P < .01) and quadratic (γ20 = 0.43; P < .01) terms were significant, which indicated that depressive symptoms were highest in young adulthood, decreased across middle adulthood, and increased again in older adulthood. The subscales followed a similar pattern. Women reported more depressed affect at younger ages, but an interaction with age suggested that this gap disappeared in old age. Accounting for comorbidity, functional limitations, and impending death slightly reduced but did not eliminate the uptick in depressive symptoms in old age.Symptoms of depression follow a U-shaped pattern across adulthood. Older adults experience an increase in distress that is not due solely to declines in physical health or approaching death.
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Recently, in the view of network analysis, depression has been conceptualized as a complex and dynamic network model combining individual symptoms. To date, no studies have systematically examined and compared depressive symptom networks across different populations.A total of 36,105 participants were recruited and asked to complete the Patient Health Questionnaire-9 among junior high school students, senior high school students, college students, and elderly adults who were more susceptible to depression during the COVID-19 lockdown in China. In the analysis, we applied the optimal cutoff score ≥ 8 for students and a score ≥ 6 for elderly adults to identify 5830 participants who were likely to be depressed. The index of "strength" was used to identify central symptoms in the network structure.The results showed that Sad Mood was the most central symptom among junior high school students, senior high school students, and college students, but the most central symptom in the elderly was Guilt. Among the top three central symptoms, Suicide Ideation was unique to senior high school students, while Anhedonia was most prevalent among college students. Guilt - Suicide Ideation, Anhedonia - Energy, Anhedonia - Sad Mood, and Sleep - Energy showed the strongest association among junior and senior high school students, college students, and elderly adults, respectively. NCT (i.e., Network Comparison Test) suggested that the network's global connectivity was ultimately inconsistent, but the network structure remained roughly intact.In treatment, targeting central symptoms may be critical to alleviating depression.Copyright © 2022 Elsevier B.V. All rights reserved.
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Loneliness is prevalent in adolescents. Although it can be a normative experience, children and adolescents who experience loneliness are often at risk for anxiety, depression, and suicide. Research efforts have been made to identify the neurobiological basis of such distressful feelings in our social brain. In adolescents, the social brain is still undergoing significant development, which may contribute to their increased and differential sensitivity to the social environment. Many behavioral studies have shown the significance of attachment security and social skills in adolescents' interactions with the social world. In this review, we propose a developmental social neuroscience model that extends from the social neuroscience model of loneliness. In particular, we argue that the social brain and social skills are both important for the development of adolescents' perceived loneliness and that adolescents' familial attachment sets the baseline for neurobiological development. By reviewing the related behavioral and neuroimaging literature, we propose a developmental social neuroscience model to explain the heightened perception of loneliness in adolescents using social skills and attachment style as neurobiological moderators. We encourage future researchers to investigate adolescents' perceived social connectedness from the developmental neuroscience perspective.
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“Sandwich grandparents” are middle-aged and older adults who have both living parents (or parents-in-law) and young grandchildren. They are faced with competing demands for caregiving from multiple generations. This study examines the prevalence, trends, and patterns of caregiving by sandwich grandparents in China. Drawing on nationally representative longitudinal data, this study estimates that more than 150 million Chinese adults aged 45 and older were sandwich grandparents in 2011. Among them, more than 17 million were dual caregivers who provided care to their own older parents and young grandchildren simultaneously. These numbers fluctuated considerably between 2011 and 2018. This study further tests the associations between three aspects of intergenerational solidarity and caregiving patterns among Chinese sandwich grandparents. Longitudinal regression analysis reveals a significant association between normative solidarity and intergenerational caregiving, but no evidence of functional or structural solidarity at work.
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This study evaluates the measurement noninvariance, or differential item functioning (DIF), in the Center for Epidemiological Studies-Depression (CES-D) items attributable to age, sex, and race/ethnicity among community-dwelling older adults. Participants (N=2773) were from the New Haven site of the Established Populations for Epidemiologic Studies in the Elderly. Statistical analyses included exploratory factor analysis, bi-factor confirmatory factor analysis, and a bi-factor multiple indicator and multiple causes (MIMIC) model to address measurement noninvariance. Blacks, compared with whites, were more likely to endorse items loading on the interpersonal factor, which include "people dislike me" and "people are unfriendly." Women were less likely to endorse the interpersonal items and the "I felt like a failure" item (odds ratio [OR]=0.63, 95% confidence interval [CI]: 0.42, 0.94) than men. But women had a higher proportional odds than men for endorsing the "crying" item (OR=1.86, 95% CI: 1.17, 2.96). Those 75 years and older (relative to those aged 65-74) were less likely to endorse the "I felt like a failure" item (OR=0.65, 95% CI: 0.43, 0.97). However, measurement noninvariance found in both the "crying" and "failure" items were attributable to women and to those aged 75 and older were trivial after controlling for the underlying level of depressive symptomatology. Therefore, the interpersonal items showed measurement noninvariance attributable to sex and race. The bi-factor MIMIC model is useful for examining measurement noninvariance due to sociodemographics in a multidimensional depression instrument.
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The experiences of emerging adulthood may vary in different historical and cultural contexts. Little research has been dedicated to how non college students view adulthood in developing countries. Currently, millions of young people are migrating from rural villages to industrial cities in China. The purpose of this study was to investigate conceptions of adulthood among Chinese migrant women workers, using mixed methods. One hundred and nineteen women workers (aged 18–29 years) from a factory in Guangdong, China, completed a questionnaire of markers for adulthood. Then, 15 of them were interviewed regarding their understanding of the transition to adulthood. The results showed that the majority of the young Chinese migrant women workers believed they had reached adulthood in some ways but not others. Married women and women with children were more likely to perceive themselves as adults, even controlling for age. Learn to care for parents, settled into a long-term career and become capable of caring for children were ranked as the most important markers for adulthood. Participants were least likely to feel adult when they were with their parents. The migrant women workers’ conceptions of adulthood reflected the traditional Chinese emphasis on family obligations, social relations and role transitions.
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This study aimed to examine associations between the employment of older people and mental health across demographic characteristics, socioeconomic conditions, and health status, with a focus on pensions.This study included 4,512 participants aged 60-69 from the CLASS in 2014. A multiple linear regression was conducted to investigate the association between employment and mental health. A causal forest model was applied to estimate the heterogeneous treatment effects.Employed individuals (n = 1,295) reported better mental health than their non-employed counterparts. This association displayed significant heterogeneity, primarily attributed to pensions. Those with lower pensions may be compelled to work due to financial reasons, thus offsetting the health-promotion effect of employment.Employment may benefit the mental health of older adults, which has a more significant marginal effect on those who are men, older, urban residents, without a spouse, below primary education, receiving more pensions, and less family and friend support.Copyright © 2024. Published by Elsevier Inc.
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