Frontiers in Psychiatry (Feb 2023)

Predictive potential of somatic symptoms for the identification of subthreshold depression and major depressive disorder in primary care settings

  • Xiuwen Li,
  • Xiuwen Li,
  • Xiuwen Li,
  • Huimin Zhang,
  • Huimin Zhang,
  • Huimin Zhang,
  • Huimin Zhang,
  • Xue Han,
  • Lan Guo,
  • Lan Guo,
  • Lan Guo,
  • Felicia Ceban,
  • Felicia Ceban,
  • Felicia Ceban,
  • Yuhua Liao,
  • Yuhua Liao,
  • Yuhua Liao,
  • Yuhua Liao,
  • Jingman Shi,
  • Jingman Shi,
  • Jingman Shi,
  • Wanxin Wang,
  • Wanxin Wang,
  • Wanxin Wang,
  • Yifeng Liu,
  • Weidong Song,
  • Dongjian Zhu,
  • Hongqiong Wang,
  • Hongqiong Wang,
  • Hongqiong Wang,
  • Lingjiang Li,
  • Beifang Fan,
  • Ciyong Lu,
  • Ciyong Lu,
  • Ciyong Lu,
  • Roger S. McIntyre,
  • Roger S. McIntyre,
  • Roger S. McIntyre,
  • Roger S. McIntyre,
  • Roger S. McIntyre

DOI
https://doi.org/10.3389/fpsyt.2023.999047
Journal volume & issue
Vol. 14

Abstract

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BackgroundThe presence of heterogenous somatic symptoms frequently obscures the recognition of depression in primary care. We aimed to explore the association between somatic symptoms and subthreshold depression (SD) and Major Depressive Disorder (MDD), as well as to determine the predictive potential of somatic symptoms in identifying SD and MDD in primary care.MethodsData were derived from the Depression Cohort in China study (ChiCTR registry number: 1900022145). The Patient Health Questionnaire-9 (PHQ-9) was used to assess SD by trained general practitioners (GPs), and the Mini International Neuropsychiatric Interview depression module was used to diagnose MDD by professional psychiatrists. Somatic symptoms were assessed using the 28-item Somatic Symptoms Inventory (SSI).ResultsIn total of 4,139 participants aged 18–64 years recruited from 34 primary health care settings were included. The prevalence of all 28 somatic symptoms increased in a dose-dependent manner from non-depressed controls to SD, and to MDD (P for trend <0.001). Hierarchical clustering analysis grouped the 28 heterogeneous somatic symptoms into three clusters (Cluster 1: energy-related symptoms, Cluster 2: vegetative symptoms, and Cluster 3: muscle, joint, and central nervous symptoms). Following adjustment for potential confounders and the other two clusters of symptoms, per 1 increase of energy-related symptoms exhibited significant association with SD (OR = 1.24, 95% CI, 1.18–1.31) and MDD (OR = 1.50, 95% CI, 1.41–1.60) The predictive performance of energy-related symptoms in identifying individuals with SD (AUC = 0.715, 95% CI, 0.697–0.732) and MDD (AUC = 0.941, 95% CI, 0.926–0.963) was superior to the performance of total SSI and the other two clusters (P < 0.05).ConclusionsSomatic symptoms were associated with the presence of SD and MDD. In addition, somatic symptoms, notably those related to energy, showed good predictive potential in identifying SD and MDD in primary care. The clinical implication of the present study is that GPs should consider the closely related somatic symptoms for early recognition for depression in practice.

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