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Cited by 17Anxiety, Depression, Psychometrics, Treatment, Cognitive ProcessesTreatment of Major DepressionMental Health Research Topics

Age of onset for major depressive disorder and its association with symptomatology

Cui, Lvchun, Wang, Yun, Cao, Lan, Wu, Zhiguo, Peng, Daihui, Chen, Jun, Yang, Haichen, Rong, Han +2 more·2023·Journal of Affective Disorders
DOI 10.1016/j.jad.2022.09.096
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Abstract

Background The age of onset (AOO) is a key factor for heterogeneity in major depressive disorder (MDD). Looking at the effect of AOO on symptomatology may improve clinical outcomes. This study aims to examine whether and how AOO affects symptomatology using a machine learning approach and latent profile analysis (LPA).Methods The study enrolled 915 participants diagnosed with MDD from eight hospitals across China. Depressive symptoms were assessed using the 17-item Hamilton Depression Rating Scale. The relationship between symptom profiles and AOO was explored using Random Forest. The effect of AOO on symptom clusters and subtypes was investigated using multiple linear regression and LPA. A continuous AOO indicator was used to conduct the analyses.Results Based on the Random Forest, symptom profiles were closely associated with AOO. The regression model showed that the severity of neurovegetative symptoms was positively associated with AOO (β = 0.18, p < 0.001), and the severity of cognitive-behavioral symptoms was negatively associated with AOO (β = -0.12, p < 0.001). LPA demonstrated that the subgroups characterized by suicide and guilt had earlier onset of depression. The subgroup with the lowest global severity of depression had the latest onset.Limitations AOO was recalled retrospectively. The relative scarcity of participants with childhood and adolescence onset depression.Conclusions AOO has an important impact on symptomatology. The findings may enhance clinical evaluations for MDD and assist clinicians in promoting earlier detection and individualized care in vulnerable individuals.

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Authors
Cui, L., Wang, Y., Cao, L., Wu, Z., Peng, D., Chen, J., Yang, H., Rong, H., Liu, T., & Fang, Y.
Affiliations
  • Shanghai Jiao Tong University (CN)
  • Qingdao University (CN)
  • Shenzhen KangNing Hospital (CN)
Corresponding author
Fang, Yiru
ORCID
Venue
Journal of Affective Disorders
Publisher
Elsevier BV
Published
2023-01
Volume
320
Pages
682-690
ISSN
0165-0327 (ISSN-L)
DOI
10.1016/j.jad.2022.09.096
OpenAlex
W4298008884
Cited by
17
References
48
Citations by year
2026: 5 · 2025: 4 · 2024: 3 · 2023: 5
FWCI
2.76
Type
journal article
Language
en
Open access
closed
Licence
Locations
  • Journal of Affective Disorders (publishedVersion)
  • PubMed (publishedVersion)
Topics
  • Social Sciences › Psychology › Experimental and Cognitive Psychology › Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes
  • Health Sciences › Medicine › Pharmacology › Treatment of Major Depression
  • Social Sciences › Psychology › Experimental and Cognitive Psychology › Mental Health Research Topics
Keywords
major depressive disorder, age of onset, depressive symptom profiles, symptom clusters, neurovegetative symptoms, suicide, guilt, depression subtypes, childhood-onset depression, adolescent-onset depression
MeSH terms
Machine Learning, Adolescent, Child, China, Major Depressive Disorder, Depressive Disorder, Major, Humans, Retrospective Studies, Age of Onset

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