AUTHOR=Li Xiuwen , Zhang Huimin , Han Xue , Guo Lan , Ceban Felicia , Liao Yuhua , Shi Jingman , Wang Wanxin , Liu Yifeng , Song Weidong , Zhu Dongjian , Wang Hongqiong , Li Lingjiang , Fan Beifang , Lu Ciyong , McIntyre Roger S. TITLE=Predictive potential of somatic symptoms for the identification of subthreshold depression and major depressive disorder in primary care settings JOURNAL=Frontiers in Psychiatry VOLUME=14 YEAR=2023 URL=https://www.frontiersin.org/journals/psychiatry/articles/10.3389/fpsyt.2023.999047 DOI=10.3389/fpsyt.2023.999047 ISSN=1664-0640 ABSTRACT=Background

The 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.

Methods

Data 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).

Results

In 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).

Conclusions

Somatic 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.