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Using network analysis to illuminate the intergenerational transmission of adversity

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Using network analysis to illuminate the intergenerational transmission of adversity. / Hemady, Chad Lance; Speyer, Lydia Gabriela; Kwok, Janell et al.
In: European journal of psychotraumatology, Vol. 13, No. 2, 2101347, 31.12.2022, p. 2101347.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Harvard

Hemady, CL, Speyer, LG, Kwok, J, Meinck, F, Melendez-Torres, GJ, Fry, D, Auyeung, B & Murray, AL 2022, 'Using network analysis to illuminate the intergenerational transmission of adversity', European journal of psychotraumatology, vol. 13, no. 2, 2101347, pp. 2101347. https://doi.org/10.1080/20008198.2022.2101347

APA

Hemady, C. L., Speyer, L. G., Kwok, J., Meinck, F., Melendez-Torres, G. J., Fry, D., Auyeung, B., & Murray, A. L. (2022). Using network analysis to illuminate the intergenerational transmission of adversity. European journal of psychotraumatology, 13(2), 2101347. Article 2101347. https://doi.org/10.1080/20008198.2022.2101347

Vancouver

Hemady CL, Speyer LG, Kwok J, Meinck F, Melendez-Torres GJ, Fry D et al. Using network analysis to illuminate the intergenerational transmission of adversity. European journal of psychotraumatology. 2022 Dec 31;13(2):2101347. 2101347. Epub 2022 Aug 18. doi: 10.1080/20008198.2022.2101347

Author

Hemady, Chad Lance ; Speyer, Lydia Gabriela ; Kwok, Janell et al. / Using network analysis to illuminate the intergenerational transmission of adversity. In: European journal of psychotraumatology. 2022 ; Vol. 13, No. 2. pp. 2101347.

Bibtex

@article{ee0c1d7832c5434995fc1cafd0750d91,
title = "Using network analysis to illuminate the intergenerational transmission of adversity",
abstract = "UNLABELLED: Objective: 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). Methods: We used data from the Avon Longitudinal Study of Parents and Children (ALSPAC) ( n  = 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. Results: 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. HIGHLIGHTS: 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.",
keywords = "ALSPAC, Intergenerational transmission of adversity, low birthweight, maternal adverse childhood experiences, maternal health, neonatal health, network analysis, pairwise Markov Random Field models, preterm birth",
author = "Hemady, {Chad Lance} and Speyer, {Lydia Gabriela} and Janell Kwok and Franziska Meinck and Melendez-Torres, {G J} and Deborah Fry and Bonnie Auyeung and Murray, {Aja Louise}",
year = "2022",
month = dec,
day = "31",
doi = "10.1080/20008198.2022.2101347",
language = "English",
volume = "13",
pages = "2101347",
journal = "European journal of psychotraumatology",
issn = "2000-8066",
publisher = "Taylor and Francis Ltd.",
number = "2",

}

RIS

TY - JOUR

T1 - Using network analysis to illuminate the intergenerational transmission of adversity

AU - Hemady, Chad Lance

AU - Speyer, Lydia Gabriela

AU - Kwok, Janell

AU - Meinck, Franziska

AU - Melendez-Torres, G J

AU - Fry, Deborah

AU - Auyeung, Bonnie

AU - Murray, Aja Louise

PY - 2022/12/31

Y1 - 2022/12/31

N2 - UNLABELLED: Objective: 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). Methods: We used data from the Avon Longitudinal Study of Parents and Children (ALSPAC) ( n  = 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. Results: 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. HIGHLIGHTS: 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.

AB - UNLABELLED: Objective: 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). Methods: We used data from the Avon Longitudinal Study of Parents and Children (ALSPAC) ( n  = 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. Results: 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. HIGHLIGHTS: 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.

KW - ALSPAC

KW - Intergenerational transmission of adversity

KW - low birthweight

KW - maternal adverse childhood experiences

KW - maternal health

KW - neonatal health

KW - network analysis

KW - pairwise Markov Random Field models

KW - preterm birth

U2 - 10.1080/20008198.2022.2101347

DO - 10.1080/20008198.2022.2101347

M3 - Journal article

C2 - 36016844

VL - 13

SP - 2101347

JO - European journal of psychotraumatology

JF - European journal of psychotraumatology

SN - 2000-8066

IS - 2

M1 - 2101347

ER -