Dimensional early life adversity and anxiety symptoms: A network analysis and longitudinal study

Zhao-Ying Wang; Shi-Xiong Hu; Jian Lu; Wen Shang; Tao Chen; Rui-Ting Zhang

doi:10.1016/j.chiabu.2024.107201

Dimensional early life adversity and anxiety symptoms: A network analysis and longitudinal study

Child Abuse Negl. 2024 Dec 27:160:107201. doi: 10.1016/j.chiabu.2024.107201. Online ahead of print.

Authors

Zhao-Ying Wang¹, Shi-Xiong Hu², Jian Lu³, Wen Shang⁴, Tao Chen⁵, Rui-Ting Zhang⁶

Affiliations

¹ Department of Psychology, Hunan Normal University, Changsha, China; Cognition and Human Behavior Key Laboratory of Hunan Province, Hunan Normal University, Changsha, China; Institute of Interdisciplinary Studies, Hunan Normal University, Changsha, China; Center for Mind & Brain Sciences, Hunan Normal University, Changsha, China.
² Shuda College, Hunan Normal University, Changsha, China.
³ Counseling and Psychological Services, Hunan Normal University, Changsha, China.
⁴ Institute of Marxism, Central South University, Changsha, China.
⁵ The University of Sydney, Brain and Mind Centre, Sydney, Australia.
⁶ Department of Psychology, Hunan Normal University, Changsha, China; Cognition and Human Behavior Key Laboratory of Hunan Province, Hunan Normal University, Changsha, China; Institute of Interdisciplinary Studies, Hunan Normal University, Changsha, China; Center for Mind & Brain Sciences, Hunan Normal University, Changsha, China. Electronic address: [email protected].

PMID: 39731875
DOI: 10.1016/j.chiabu.2024.107201

Abstract

Background: Accumulating literature has found a close relation between early life adversity (ELA) and anxiety. However, previous studies did not rule out the high co-occurrence of different types of ELA when exploring the association of ELA and anxiety. In the present study, we carried out network analysis based on a cross-sectional sample and longitudinal sample to investigate the relationship between ELA and anxiety symptoms in non-clinical populations over time.

Methods: Online advertisement was carried out to recruit participants. The cross-sectional sample included 871 Chinese participants (M_age = 19.11, SD_age = 1.57), and the longitudinal sample involved 440 Chinese participants (M_age = 18.93, SD_age = 0.75). Three dimensions of ELA were assessed. The Threat/Harm dimension was assessed by subscales of physical abuse, emotional abuse, and sexual abuse of Childhood Trauma Questionnaire (CTQ). The Deprivation dimension of ELA was measured by subscales of physical neglect, and emotional neglect of CTQ. The Unpredictability dimension of ELA was evaluated by the Childhood Unpredictability scale. Anxiety symptoms were captured by the Generalized Anxiety Disorder-7 (GAD-7). Regularized partial correlation networks were constructed, and the expected influence (EI) as well as predictability of each node were calculated. Stability within the network was tested and the network comparison test was conducted to examine the difference between the cross-sectional network and the longitudinal network.

Results: The cross-sectional network was relatively tight, and nodes within the dimension of ELA clustered together. Childhood unpredictability and emotional abuse revealed stronger associations with anxiety symptoms than other ELAs. Emotional abuse showed the highest EI in the network. These findings were replicated in the longitudinal network. The network comparison test indicated no significant difference between the cross-sectional network and the longitudinal network.

Conclusion: Childhood unpredictability and emotional abuse were strong predictors of anxiety symptoms, and the prediction was reliable and persistent. Reduce the experience of childhood emotional abuse can serve as a target to prevent anxiety.

Keywords: Anxiety symptoms; Childhood abuse; Childhood neglect; Childhood unpredictability; Early life adversity; Network analysis.