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About this paper symposium
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| Panel 26. Solicited Content: Displacement Related |
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| Biological signatures of war and displacement: A review with future directions for research and practice | |||
| Author information | Role | ||
| Jelena Jankovic-Rankovic, Department of Anthropology, University of South Carolina, United States | Presenting author | ||
| Catherine Panter-Brick, Department of Anthropology, Yale University; Jackson School of Global Affairs, Yale University, United States | Non-presenting author | ||
| Abstract | |||
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Introduction. Globally, 117.3 million people have been forcefully displaced, many facing adversities that result in toxic stress, trauma, and potentially altered epigenetic development. Violence, climate-related crises, and human rights violations drive this significant global issue. In their pursuit of safety across international borders, many refugees encounter challenging conditions that negatively impact their biological and psychosocial well-being. Methods. This paper employs a narrative review methodology to synthesize knowledge on the genetic, epigenetic, and physiological impacts of war trauma and forced displacement. It focuses on peer-reviewed studies published between January 2000 and March 2024. Publications were identified using key terms related to forced migration, health, war, refugees, and biomarkers across Scopus, DOAJ, PubMed, and Google Scholar databases. Out of 52 studies identified, 36 publications and one article under review met the inclusion criteria, while non-peer-reviewed, non-English, and mental health-focused studies without genetic or physiological data were excluded. Results. Most of the research was conducted in Europe (n=12) and the Middle East (n=11), primarily focusing on adults (n=24), and published after 2015 (n=30). Most publications were cross-sectional (n=25), followed by experimental (n=1) and observational (n=11). Biomarkers, including cortisol, DHEA, and neurotrophins, were assessed using various biological samples, while genetic and epigenetic markers were analyzed through saliva, buccal, and blood DNA. The studies revealed heterogeneous findings regarding biological responses to war adversities and their links to health outcomes. Cross-sectional studies revealed different cortisol levels in saliva, urine, blood, hair, and fingernails, indicating both heightened and diminished cortisol responses among refugees, influenced by the timing and nature of trauma. Similarly, fluctuating levels of other biomarkers, including DHEA, cellular immunity, inflammation, and neuroplasticity markers, were recorded and linked to factors such as past trauma, mental health treatment, and environmental conditions. Only one study provided experimental evidence from randomized control trials involving refugee and non-refugee youth. It evaluated the effectiveness of a youth program in alleviating toxic stress, revealing a significant 33% reduction in cortisol levels over time among war-affected adolescents in the intervention group compared to controls. Observational studies further highlighted the complexity and variability of biological responses to trauma due to genetic factors, previous trauma, and environmental conditions. Genomic research exploring the effects of early-life adversities and maternal trauma on health showed inconsistent findings regarding maternal stress, trauma, and DNA methylation patterns. While studies on refugee youth suggest that genetic factors interact with stress to affect mental health outcomes, intergenerational studies indicate potential links between maternal PTSD and children’s biological markers, suggesting trauma transmission across generations through epigenetic mechanisms. Conclusion. These findings highlight four key observations: the importance of physiological and genomic biomarkers in tracking responses to war trauma; the necessity of strengthening research designs to clarify causality and support health-promoting interventions; the need to address ethical challenges; and the requirement for a detailed consideration of theoretical frameworks and research methods in scholarly publications. Addressing these aspects can help create a roadmap for assessing interventions and their positive effects on health and physiology in forcibly displaced communities. |
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| Paper #2 | |
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| Intergenerational Patterns of Biobehavioral Dysregulation in War-Affected Families in Sierra Leone | |
| Author information | Role |
| Dr. Candace Jasmine Black, Ph.D., Boston College School of Social Work, United States | Presenting author |
| Abdulai Jawo Bah, Boston College School of Social Work, Sierra Leone | Non-presenting author |
| Wijnand Van Den Boom, Boston College School of Social Work, United States | Non-presenting author |
| Kashiya Nwanguma, Boston College School of Social Work, Sierra Leone | Non-presenting author |
| Alberta Bonney, Boston College School of Social Work, Sierra Leone | Non-presenting author |
| Theresa S. Betancourt, Boston College School of Social Work, United States | Non-presenting author |
| Abstract | |
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Introduction: More than 1.7 billion children live in countries affected by armed conflict while one in six live directly in conflict zones—the majority of whom are in Sub-Saharan Africa. Conflict-affected children face extreme poverty, malnutrition, preventable diseases, fewer social and economic opportunities, and severely under-resourced mental healthcare. Furthermore, war trauma has pervasive effects on emotional and cognitive development, and can interfere with healthy interpersonal relationships and the pursuit of education and gainful employment. These difficulties often persist long after the end of a conflict and, remarkably, may even be mirrored in the next generation. Understanding the mechanisms that underpin this intergenerational transmission may shed light on potential levers that could interrupt these cycles. Hypotheses: We hypothesize that patterns of biobehavioral dysregulation (e.g., self-regulation, stress reactivity via heart rate variability, inflammation, telomere erosion) will be similar among former war-affected youth who have become parents and their biological children. Study Population: Data are drawn from the Intergenerational Study of War-Affected Youth, a 22-year study that has extensively documented the experiences of children conscripted into armed groups (“child soldiers”) and other war-affected youth since the end of the Civil War in Sierra Leone (1991-2002). Our fifth wave of data collection, currently underway, will re-enroll 394 former war-affected youth who have become parents and 410 offspring aged 7-24. Projected estimates of sample characteristics indicate that caregivers are 56% female with a mean age of 34.7 (SD = 5.45) while children are 52% female with a mean age of 12.74 (SD=4.25). Methods: Participants are visited at home by staff from our local partner NGO. Staff conduct structured interviews in Krio on an extensive survey battery that includes measures of trauma exposure, mental health, and risk and protective factors at the individual, family, and community levels. Wave 5 is the first wave to measure stress biomarkers, including autonomic stress reactivity, inflammation, and telomere length, as well as a physical health assessment. Stress reactivity is measured with respiratory sinus arrhythmia (RSA) during caregiver-child dyadic interactions. Inflammatory markers and telomere length will be collected via dried blood spot. Results: Our preliminary analysis from Wave 4 data indicate that disruptions in emotion regulation and mental health experienced by former war-affected youth who have become parents are shared in their biological offspring. We will extend this research by examining associations among self-regulation, stress reactivity, inflammation, and telomere erosion in parents exposed to the war and their biological children who were not directly exposed to the war. This research lays the groundwork for understanding how risk and protective factors across the social ecology may be involved in the persistence of biobehavioral dysregulation across generations. |
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| Paper #3 | |
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| Biological Embedding of Adversity Related to Forced Displacement: Predicting Infant Parasympathetic Regulation Using Machine Learning | |
| Author information | Role |
| Elisa Ugarte, Global TIES for Children, Chile | Presenting author |
| Duja Michael, Global TIES for Children, United States | Non-presenting author |
| Eamam Hossain, icddr,b, Bangladesh | Non-presenting author |
| Md Shakil Ahamed, icddr,b, Bangladesh | Non-presenting author |
| Mahbub Elahi, icddr,b, Bangladesh | Non-presenting author |
| Paul D. Hastings, Department of Psychology, University of California Davis, United States | Non-presenting author |
| Fahmida Tofail, icddr,b, Bangladesh | Non-presenting author |
| Alice Wuermli, Global TIES for Children, New York University, United States | Non-presenting author |
| Abstract | |
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Introduction. War and conflict have displaced over 117 million people worldwide, with 40% being children (UNHCR, 2024). In the Rohingya refugee camps in Bangladesh, home now to nearly 1 million people fleeing genocide, thousands of Rohingya women have given birth and raised children within these refugee camps. Exposure to war, displacement, and harsh camp environments often lead to poor mental health, such as depression, anxiety, and PTSD, which during the prenatal period may jeopardize fetal and infant development. One key area of concern is the infant's ability to regulate their autonomic physiology, particularly through the parasympathetic nervous system (PNS), indexed by respiratory sinus arrhythmia (RSA). PNS regulation rapidly develops from the 3rd trimester to the first several months after birth, with ample opportunity to be shaped through prenatal factors and early experiences. While previous research has examined individual predictors of RSA, this exploratory study leverages machine learning (ML) to assess how a combination of environmental, biological, and social factors collectively influence infant resting RSA. ML allows for non-linear patterns and interactions across a wide range of variables, even with small sample sizes, providing a more accurate prediction of RSA compared to traditional models. Methods. The sample included 83 infants (58% male) aged approximately 43 days (min=25, max=96), born to mothers who were, on average, 19 years old (78% Rohingya, min=14, max=37). Infant RSA was measured during a solo 3-minute baseline, and multi-level predictors included sociodemographic factors, environmental exposures, maternal mental health, birth anthropometrics, and social support (npredictors = 99, Table 1). We tested linear models (ElasticNet, Support Vector Linear) and non-linear models (Random Forest, Support Vector Radial, Gradient Boosted Trees) to identify which method and set of predictors maximized the prediction of infant RSA. Results. Non-linear models achieved the best predictive performance, with gradient-boosted trees outperforming all others (R² = 0.57, MAE = 0.42). The model identified several prenatal and postnatal factors influencing infant RSA, focusing on the top 10 (Figure 1). Prenatal sleep hours emerged as a significant predictor, underscoring the role of maternal sleep in shaping infant physiological regulation. Head circumference, length-for-age, and MUAC at birth were also important, highlighting the contribution of early physical development to autonomic regulation. Prenatal blood pressure and child arousal state further influenced RSA. Other relevant factors included husband age and antenatal care initiation, reflecting broader social and health dynamics. Finally, maternal war trauma exposure had a notable impact, suggesting that the stress of war and displacement can have lasting effects on infant development. Conclusion. These preliminary findings highlight the value of ML in identifying critical prenatal and postnatal factors that influence infant parasympathetic nervous system regulation. For future analyses (March), we plan to expand the sample size and include maternal RSA to account for potential hereditary influences on infant physiological regulation. Leveraging ML allows us to integrate complex, multi-level data, enabling more precise predictions of developmental outcomes in vulnerable populations. Continued research in this area will inform targeted interventions to improve prenatal care and infant health, particularly in conflict-affected populations. |
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Biological Embedding of Trauma in War and Displacement: Intergenerational Mechanisms and Innovations
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Paper Symposium
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| Session Title | Biological Embedding of Trauma in War and Displacement: Intergenerational Mechanisms and Innovations |