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Background <p>The long-term influence of distinct adverse childhood experiences (ACEs) patterns on heterogeneous trajectories of successful aging (SA) remains unclear.</p> Methods <p>Using 2011–2018 China Health and Retirement Longitudinal Study data from 3,092 community-dwelling older adults (aged ≥ 60), latent class analysis identified four distinct ACE patterns from 13 binary indicators based on exposure probabilities, clinical significance, and prior literature. SA was evaluated across five domains: absence of chronic disease, no disability, high cognition, no depressive symptoms, and active social engagement. As SA represents a heterogeneous outcome dynamically evolving over time during aging, group-based trajectory modeling mapped its eight-year trajectories, which were linked to baseline latent ACE classes via logistic regression. Finally, network analysis using the graphical lasso algorithm compared network structure, global strength, edge weights, and node centrality of SA domains between trajectory groups to investigate interaction patterns.</p> Results <p>We identified four ACEs patterns (Low Adversity, 54.2%; Maltreatment, 21.7%; Household Dysfunction, 20.0%; Pervasive Adversity, 4.1%) and two successful aging trajectories (Sustained High-Decline, 22%; Chronically Low-Stable, 78%). Compared to the Low Adversity pattern, the Pervasive Adversity [OR = 1.97, 95% CI (1.10, 3.83)] and Household Dysfunction [OR = 1.36, 95% CI (1.07, 1.74)] patterns were associated with the adverse Chronically Low-Stable trajectory, whereas the Maltreatment pattern showed no significant longitudinal association. Low educational attainment was the strongest predictor of this adverse trajectory [OR = 5.23, 95% CI (3.84, 7.13)]. Network analysis indicated differences in overall network structure between trajectory groups (<i>p</i> = 0.037) but not in global strength. Specifically, compared to Sustained High-Decline, the Chronically Low-Stable group exhibited a more rigid network with a stronger Cognition-Chronic Disease edge weight (<i>p</i> &lt; 0.001) but lower Cognition centrality (<i>p</i> &lt; 0.001).</p> Conclusions <p>Culturally specific early-life adversity patterns, particularly household dysfunction and pervasive adversity, predict adverse successful aging trajectories. These childhood patterns are associated with a more rigid late-life mind-body network characterized by tight pathological coupling between cognition and physical illness. Importantly, broader structural inequalities across the life course, particularly low educational attainment and rural residence, operate alongside early-life trauma as dominant predictors of adverse aging trajectories, highlighting the need for systemic, policy-level interventions.</p>

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Association of adverse childhood experiences patterns with successful aging trajectories: a prospective cohort study

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月24日

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  • Kunhao Yang,
  • Xin Yang,
  • Hui Fan,
  • Lidan Zheng,
  • Xiangli Zeng

摘要

Background

The long-term influence of distinct adverse childhood experiences (ACEs) patterns on heterogeneous trajectories of successful aging (SA) remains unclear.

Methods

Using 2011–2018 China Health and Retirement Longitudinal Study data from 3,092 community-dwelling older adults (aged ≥ 60), latent class analysis identified four distinct ACE patterns from 13 binary indicators based on exposure probabilities, clinical significance, and prior literature. SA was evaluated across five domains: absence of chronic disease, no disability, high cognition, no depressive symptoms, and active social engagement. As SA represents a heterogeneous outcome dynamically evolving over time during aging, group-based trajectory modeling mapped its eight-year trajectories, which were linked to baseline latent ACE classes via logistic regression. Finally, network analysis using the graphical lasso algorithm compared network structure, global strength, edge weights, and node centrality of SA domains between trajectory groups to investigate interaction patterns.

Results

We identified four ACEs patterns (Low Adversity, 54.2%; Maltreatment, 21.7%; Household Dysfunction, 20.0%; Pervasive Adversity, 4.1%) and two successful aging trajectories (Sustained High-Decline, 22%; Chronically Low-Stable, 78%). Compared to the Low Adversity pattern, the Pervasive Adversity [OR = 1.97, 95% CI (1.10, 3.83)] and Household Dysfunction [OR = 1.36, 95% CI (1.07, 1.74)] patterns were associated with the adverse Chronically Low-Stable trajectory, whereas the Maltreatment pattern showed no significant longitudinal association. Low educational attainment was the strongest predictor of this adverse trajectory [OR = 5.23, 95% CI (3.84, 7.13)]. Network analysis indicated differences in overall network structure between trajectory groups (p = 0.037) but not in global strength. Specifically, compared to Sustained High-Decline, the Chronically Low-Stable group exhibited a more rigid network with a stronger Cognition-Chronic Disease edge weight (p < 0.001) but lower Cognition centrality (p < 0.001).

Conclusions

Culturally specific early-life adversity patterns, particularly household dysfunction and pervasive adversity, predict adverse successful aging trajectories. These childhood patterns are associated with a more rigid late-life mind-body network characterized by tight pathological coupling between cognition and physical illness. Importantly, broader structural inequalities across the life course, particularly low educational attainment and rural residence, operate alongside early-life trauma as dominant predictors of adverse aging trajectories, highlighting the need for systemic, policy-level interventions.