Sex differences in the network structures of depressive symptom profiles in Asian patients with depressive disorders: findings from the Research on Asian Psychotropic Patterns for Antidepressants, Phase 3.
Han Seul Kim, Seonjae Lee, Jeongha Lee, Tae Young Choi, Sung-Won Jung, Hyung-Jun Yoon, Hyun Soo Kim, Yangsik Kim, Hyun-Ju Yang, Narae Jeong, Eunsoo Moon, Daeho Kim, Tian-Mei Si, Roy Abraham Kallivayalil, Andi J Tanra, Amir Hossein Jalali Nadoushan, Kok Yoon Chee, Afzal Javed, Kang Sim, Pornjira Pariwatcharakul, Mian-Yoon Chong, Toshiya Inada, Shih-Ku Lin, Norman Sartorius, Naotaka Shinfuku, Takahiro A Kato, Jae-Hon Lee, Seon-Cheol Park
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引用次数: 0
Abstract
Background: Depression is a complex mental health disorder with highly heterogeneous symptoms that vary significantly across individuals, influenced by various factors, including sex and regional contexts. Network analysis is an analytical method that provides a robust framework for evaluating the heterogeneity of depressive symptoms and identifying their potential clinical implications.
Objective: To investigate sex-specific differences in the network structures of depressive symptoms in Asian patients diagnosed with depressive disorders, using data from the Research on Asian Psychotropic Prescription Patterns for Antidepressants, Phase 3, which was conducted in 2023.
Methods: A network analysis of 10 depressive symptoms defined according to the National Institute for Health and Care Excellence guidelines was performed. The sex-specific differences in the network structures of the depressive symptoms were examined using the Network Comparison Test. Subgroup analysis of the sex-specific differences in the network structures was performed according to geographical region classifications, including East Asia, Southeast Asia, and South or West Asia.
Results: A total of 998 men and 1,915 women with depression were analysed in this study. The analyses showed that all 10 depressive symptoms were grouped into a single cluster. Low self-confidence and loss of interest emerged as the most central nodes for men and women, respectively. In addition, a significant difference in global strength invariance was observed between the networks. In the regional subgroup analysis, only East Asian men showed two distinct clustering patterns. In addition, significant differences in global strength and network structure were observed only between East Asian men and women.
Conclusion: The study highlights the sex-specific differences in depressive symptom networks across Asian countries. The results revealed that low self-confidence and loss of interest are the main symptoms of depression in Asian men and women, respectively. The network connections were more localised in men, whereas women showed a more diverse network. Among the Asian subgroups analysed, only East Asians exhibited significant differences in network structure. The considerable effects of neurovegetative symptoms in men may indicate potential neurobiological underpinnings of depression in the East Asian population.
背景:抑郁症是一种复杂的精神健康障碍,具有高度异质性的症状,在个体之间差异很大,受各种因素的影响,包括性别和地区背景。网络分析是一种分析方法,为评估抑郁症状的异质性和确定其潜在的临床意义提供了一个强有力的框架。目的:研究亚洲抑郁症患者抑郁症状网络结构的性别差异,研究数据来自于2023年开展的“亚洲抗抑郁药物处方模式研究”(Research on Asian Psychotropic Prescription Patterns for depressive ants, Phase 3)。方法:根据国家健康和护理卓越研究所的指导方针,对10种抑郁症状进行网络分析。使用网络比较测试来检验抑郁症状网络结构的性别差异。根据地理区域分类,包括东亚、东南亚和南亚或西亚,对网络结构的性别差异进行亚群分析。结果:本研究共分析了998名男性和1915名女性抑郁症患者。分析表明,所有10种抑郁症状被归为一个单一的集群。缺乏自信和失去兴趣分别成为男性和女性最主要的节点。此外,网络之间的整体强度不变性有显著差异。在区域亚组分析中,只有东亚男性表现出两种不同的聚类模式。此外,全球力量和网络结构的显著差异仅在东亚男性和女性之间观察到。结论:该研究强调了亚洲国家抑郁症状网络的性别特异性差异。研究结果显示,亚洲男性和女性抑郁的主要症状分别是缺乏自信和失去兴趣。男性的网络连接更局部,而女性则表现出更多样化的网络。在分析的亚洲亚群中,只有东亚人在网络结构上表现出显著差异。男性神经植物症状的显著影响可能表明东亚人群抑郁症的潜在神经生物学基础。
期刊介绍:
Acta Neuropsychiatrica is an international journal focussing on translational neuropsychiatry. It publishes high-quality original research papers and reviews. The Journal''s scope specifically highlights the pathway from discovery to clinical applications, healthcare and global health that can be viewed broadly as the spectrum of work that marks the pathway from discovery to global health.