Sönmez Cemile Ceren, Verdeli Helen, Malgaroli Matteo, Delgadillo Jaime, Keller Bryan
Counseling and Clinical Psychology Department, Teachers College, Columbia University, New York, USA.
Institute for Global Health, University College London, London, UK.
Glob Ment Health (Camb). 2025 Feb 17;12:e30. doi: 10.1017/gmh.2025.16. eCollection 2025.
We present a series of network analyses aiming to uncover the symptom constellations of depression, anxiety and somatization among 2,796 adult primary health care attendees in Goa, India, a low- and middle-income country (LMIC). Depression and anxiety are the leading neuropsychiatric causes of disability. Yet, the diagnostic boundaries and the characteristics of their dynamically intertwined symptom constellations remain obscure, particularly in non-Western settings. Regularized partial correlation networks were estimated and the diagnostic boundaries were explored using community detection analysis. The global and local connectivity of network structures of public versus private healthcare settings and treatment responders versus nonresponders were compared with a permutation test. Overall, depressed mood, panic, fatigue, concentration problems and somatic symptoms were the most central. Leveraging the longitudinal nature of the data, our analyses revealed baseline networks did not differ across treatment responders and nonresponders. The results did not support distinct illness subclusters of the CMDs. For public healthcare settings, panic was the most central symptom, whereas in private, fatigue was the most central. Findings highlight varying mechanism of illness development across socioeconomic backgrounds, with potential implications for case identification and treatment. This is the first study directly comparing the symptom constellations of two socioeconomically different groups in an LMIC.
我们展示了一系列网络分析，旨在揭示印度果阿邦2796名成年初级卫生保健就诊者中抑郁、焦虑和躯体化的症状群，印度是一个低收入和中等收入国家（LMIC）。抑郁和焦虑是导致残疾的主要神经精神原因。然而，它们动态交织的症状群的诊断界限和特征仍然模糊不清，尤其是在非西方背景下。我们估计了正则化偏相关网络，并使用社区检测分析探索了诊断界限。通过置换检验比较了公立与私立医疗保健机构以及治疗反应者与无反应者的网络结构的全局和局部连通性。总体而言，情绪低落、恐慌、疲劳、注意力不集中问题和躯体症状最为核心。利用数据的纵向性质，我们的分析表明，治疗反应者和无反应者的基线网络没有差异。结果不支持常见精神障碍的不同疾病亚群。对于公立医疗保健机构，恐慌是最核心的症状，而在私立机构中，疲劳是最核心的。研究结果突出了不同社会经济背景下疾病发展的不同机制，对病例识别和治疗具有潜在影响。这是第一项直接比较低收入和中等收入国家中两个社会经济不同群体症状群的研究。
