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Background <p>Depressive symptoms among middle-aged and older adults are a significant public health concern, with varying symptom trajectories over time. Understanding these trajectories and their predictors can inform targeted interventions.</p> Objectives <p>To identify subgroups of depressive symptom trajectories, determine predictors of these subgroups, and explore the core symptoms and their predictive relationships.</p> Methods <p>This study analyzed 7,166 participants aged ≥ 45 years from the China Health and Retirement Longitudinal Study across four waves (2011, 2013, 2015, 2018). Depressive symptoms were assessed using the 10-item Center for Epidemiologic Studies Depression Scale. Group-based trajectory modeling (GBTM) identified depressive symptom trajectories. Multivariate logistic regression explored influencing factors, while Cross-lagged panel network models (CLPN) were used to identify core symptoms.</p> Results <p>Three distinct trajectory groups were identified: “<i>stable low</i>” (66.4%), “<i>decline followed by an increase</i>” (27.8%), and “<i>continuously rising</i>” (5.8%). Females, those with lower education, poor self-reported health, unmarried status and rural residents were associated with worsening symptoms. CLPN analysis revealed “<i>depressive mood</i>” as the core symptom, with “<i>feeling lonely</i>” and “<i>could not get going</i>” predicting “<i>depressive mood</i>.”</p> Conclusion <p>This study identifies distinct trajectories of depressive symptoms in older adults and pinpoints “depressive mood” as a core symptom, which is dynamically predicted by loneliness and a lack of behavioral activation. Therefore, an effective public health strategy should involve not only identifying at-risk individuals based on their trajectory profiles but also targeting these specific precursor symptoms to prevent escalation.</p>

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Trajectories of depressive symptoms in middle-aged and older Chinese adults: identifying subgroups, core symptoms and predictors

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年7月15日

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  • Jia Fang,
  • Wenwen Wu,
  • Chen Yang,
  • Huiyuan Li,
  • Wencan Cheng,
  • Ni Zhang,
  • Baoyi Zhang,
  • Ye Zhang,
  • Meifen Zhang

摘要

Background

Depressive symptoms among middle-aged and older adults are a significant public health concern, with varying symptom trajectories over time. Understanding these trajectories and their predictors can inform targeted interventions.

Objectives

To identify subgroups of depressive symptom trajectories, determine predictors of these subgroups, and explore the core symptoms and their predictive relationships.

Methods

This study analyzed 7,166 participants aged ≥ 45 years from the China Health and Retirement Longitudinal Study across four waves (2011, 2013, 2015, 2018). Depressive symptoms were assessed using the 10-item Center for Epidemiologic Studies Depression Scale. Group-based trajectory modeling (GBTM) identified depressive symptom trajectories. Multivariate logistic regression explored influencing factors, while Cross-lagged panel network models (CLPN) were used to identify core symptoms.

Results

Three distinct trajectory groups were identified: “stable low” (66.4%), “decline followed by an increase” (27.8%), and “continuously rising” (5.8%). Females, those with lower education, poor self-reported health, unmarried status and rural residents were associated with worsening symptoms. CLPN analysis revealed “depressive mood” as the core symptom, with “feeling lonely” and “could not get going” predicting “depressive mood.”

Conclusion

This study identifies distinct trajectories of depressive symptoms in older adults and pinpoints “depressive mood” as a core symptom, which is dynamically predicted by loneliness and a lack of behavioral activation. Therefore, an effective public health strategy should involve not only identifying at-risk individuals based on their trajectory profiles but also targeting these specific precursor symptoms to prevent escalation.