Hemady Chad Lance, Speyer Lydia Gabriela, Kwok Janell, Meinck Franziska, Melendez-Torres G J, Fry Deborah, Auyeung Bonnie, Murray Aja Louise
School of Social and Political Science, University of Edinburgh, Edinburgh, UK.
Department of Psychology, University of Cambridge, Cambridge, UK.
Eur J Psychotraumatol. 2022 Aug 18;13(2):2101347. doi: 10.1080/20008198.2022.2101347. eCollection 2022.
The effects of maternal exposure to adverse childhood experiences (ACEs) may be transmitted to subsequent generations through various biopsychosocial mechanisms. However, studies tend to focus on exploring one or two focal pathways with less attention paid to links between different pathways. Using a network approach, this paper explores a range of core prenatal risk factors that may link maternal ACEs to infant preterm birth (PTB) and low birthweight (LBW). We used data from the Avon Longitudinal Study of Parents and Children (ALSPAC) ( = 8379) to estimate two mixed graphical network models: Model 1 was constructed using adverse infant outcomes, biopsychosocial and environmental risk factors, forms of ACEs, and sociodemographic factors. In Model 2, ACEs were combined to represent a threshold ACEs score (≥4). Network indices (i.e., shortest path and bridge expected influence [1-step & 2-step]) were estimated to determine the shortest pathway from ACEs to infant outcomes, and to identify the risk factors that are vital in activating other risk factors and adverse outcomes. Network analyses estimated a mutually reinforcing web of childhood and prenatal risk factors, with each risk connected to at least two other risks. Bridge influence indices suggested that childhood physical and sexual abuse and multiple ACEs were highly interconnected to others risks. Overall, risky health behaviours during pregnancy (i.e., smoking & illicit drug use) were identified as 'active' risk factors capable of affecting (directly and indirectly) other risk factors and contributing to the persistent activation of the global risk network. These risks may be considered priority candidate targets for interventions to disrupt intergenerational risk transmission. Our study demonstrates the promise of network analysis as an approach for illuminating the intergenerational transmission of adversity in its full complexity.
We took a network approach to assessing links between ACEs and birth outcomes.ACEs, other prenatal risk factors, and birth outcomes had complex inter-connectionsHealth behaviours in pregnancy were indicated as optimal intervention targets.
母亲暴露于不良童年经历（ACEs）的影响可能通过各种生物心理社会机制传递给后代。然而，研究往往集中在探索一两条主要途径，而较少关注不同途径之间的联系。本文采用网络方法，探讨了一系列可能将母亲的ACEs与婴儿早产（PTB）和低出生体重（LBW）联系起来的核心产前风险因素。我们使用了来自阿冯父母与儿童纵向研究（ALSPAC）（n = 8379）的数据来估计两个混合图形网络模型：模型1使用不良婴儿结局、生物心理社会和环境风险因素、ACEs形式以及社会人口学因素构建。在模型2中，将ACEs合并以表示ACEs阈值分数（≥4）。估计网络指数（即最短路径和桥梁预期影响[1步和2步]）以确定从ACEs到婴儿结局的最短途径，并识别在激活其他风险因素和不良结局中至关重要的风险因素。网络分析估计了一个相互强化的童年和产前风险因素网络，每个风险至少与其他两个风险相关。桥梁影响指数表明，童年期身体和性虐待以及多种ACEs与其他风险高度相互关联。总体而言，孕期的危险健康行为（即吸烟和使用非法药物）被确定为能够（直接和间接）影响其他风险因素并导致全球风险网络持续激活的“活跃”风险因素。这些风险可能被视为干预以中断代际风险传递的优先候选目标。我们的研究证明了网络分析作为一种全面揭示逆境代际传递复杂性的方法的前景。
我们采用网络方法评估ACEs与出生结局之间的联系。ACEs、其他产前风险因素和出生结局具有复杂的相互联系。孕期健康行为被指出是最佳干预目标。
