Background Adverse Childhood Experiences (ACEs) are a common pathway to adult depression. This pathway is particularly important during the perinatal period when women are at an elevated risk for depression. However, this relationship has not been explored in South Asia. This study estimates the association between ACEs and women’s (N = 889) depression at 36 months postpartum in rural Pakistan. Method Data come from the Bachpan Cohort study. To capture ACEs, an adapted version of the ACE-International Questionnaire was used. Women’s depression was measured using both major depressive episodes (MDE) and depressive symptom severity. To assess the relationship between ACEs and depression, log-Poisson models were used for MDE and linear regression models for symptom severity. Results The majority (58%) of women experienced at least one ACE domain, most commonly home violence (38.3%), followed by neglect (20.1%). Women experiencing four or more ACEs had the most pronounced elevation of symptom severity (β = 3.90; 95% CL = 2.13, 5.67) and MDE (PR = 2.43; 95% CL = 1.37, 4.32). Symptom severity (β = 2.88; 95% CL = 1.46, 4.31), and MDE (PR = 2.01; 95% CL = 1.27, 3.18) were greater for those experiencing community violence or family distress (β = 2.04; 95%; CL = 0.83, 3.25) (PR = 1.77; 95% CL = 1.12, 2.79). Conclusions Findings suggest that ACEs are substantively distinct and have unique relationships to depression. They signal a need to address women’s ACEs as part of perinatal mental health interventions and highlight women’s lifelong experiences as important factors to understanding current mental health. Trial registration NCT02111915. Registered 11 April 2014. NCT02658994. Registered 22 January 2016. Both trials were prospectively registered.
Aim: Maximizing the utility and equity of genomic sequencing integration in clinical care requires engaging patients, their families, and communities. The NCGENES 2 study explores the impact of engagement between clinicians and caregivers of children with undiagnosed conditions in the context of a diagnostic genomic sequencing study. Methods: A Community Consult Team (CCT) of diverse parents and advocates for children with genetic and/or neurodevelopmental conditions was formed. Results: Early and consistent engagement with the CCT resulted in adaptations to study protocol and materials relevant to this unique study population. Discussion: This study demonstrates valuable contributions of community stakeholders to inform the implementation of translational genomics research for diverse participants.
Summary: Advances in technologies to measure a broad set of exposures have led to a range of exposome research efforts. Yet, these efforts have insufficiently integrated methods that incorporate genetic data to strengthen causal inference, despite evidence that many exposome-associated phenotypes are heritable. Objective: We demonstrate how integration of methods and study designs that incorporate genetic data can strengthen causal inference in exposomics research by helping address six challenges: reverse causation and unmeasured confounding, comprehensive examination of phenotypic effects, low efficiency, replication, multilevel data integration, and characterization of tissue-specific effects. Examples are drawn from studies of biomarkers and health behaviors, exposure domains where the causal inference methods we describe are most often applied. Discussion: Technological, computational, and statistical advances in genotyping, imputation, and analysis, combined with broad data sharing and cross-study collaborations, offer multiple opportunities to strengthen causal inference in exposomics research. Full application of these opportunities will require an expanded understanding of genetic variants that predict exposome phenotypes as well as an appreciation that the utility of genetic variants for causal inference will vary by exposure and may depend on large sample sizes. However, several of these challenges can be addressed through international scientific collaborations that prioritize data sharing. Ultimately, we anticipate that efforts to better integrate methods that incorporate genetic data will extend the reach of exposomics research by helping address the challenges of comprehensively measuring the exposome and its health effects across studies, the life course, and in varied contexts and diverse populations. https://doi.org/10.1289/EHP9098
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