Identifying the longitudinal outcomes of suicide loss in a population-based cohort - PROJECT ABSTRACT
The impact of suicide reaches well-beyond individual suicide decedents. For each suicide death, an estimated
135 people are exposed to the potential trauma of suicide loss. Research indicates that exposure to suicide
loss can result in mental and physical health distress, with those experiencing adverse outcomes called
“suicide loss survivors.” At the same time, the literature is severely limited by a lack of appropriate comparison
groups (e.g., accident death loss), examining a limited number of outcomes without considering comorbidity,
and focusing on one type of familial relation (e.g., spouses) while ignoring non-familial loss survivors (e.g.,
cohabitants). Consequently, the lack of high-quality population-level longitudinal epidemiologic studies of
suicide loss survivors hinders our ability to understand the full health effects of suicide and the full extent of the
suicide public health crisis. The overall goal of this project is to use Danish national registry data to document
the mental and physical health outcomes and comorbidities among the population of individuals exposed to
suicide loss over a 30-year period. Denmark has a universal healthcare system, with government supported
nationwide electronic health and social registries, and the ability to link records across registries and
individuals using unique personal/family identifiers and address information. Our project will leverage the
registries to directly address gaps in the suicide loss literature. We will develop a cohort of all first-degree
relatives and cohabitants exposed to suicide loss between 1994 and 2024, as well as two comparison cohorts
(1) exposed to accident loss, and (2) from the general population (Aim 1). The cohorts will include all available
socio-demographic and electronic medical record data over the 30-year follow-up period. These data will be
used to conduct an epidemiologic outcome-wide analysis of suicide loss (Aim 2). We will identify all mental and
physical health ICD-coded diagnostic outcomes that are specific to suicide loss (compared to accident loss and
the general population), and examine how outcomes vary by time since loss, relationship type, and sex. This
approach will inform novel and more precise targets for prevention and intervention within the field of suicide
postvention. The cohort also will be used to identify the most salient patterns of diagnostic comorbidity that
follow suicide loss (Aim 3). Unsupervised machine learning will identify latent subgroups of suicide loss
survivors characterized by common patterns of mental and physical health comorbidity, with the goal of
informing transdiagnostic prevention/treatment and generating mechanistic hypotheses. This study is an
efficient way to lay a foundation for the epidemiology of suicide loss. Our results will provide clinicians and
policymakers with the information needed to design and study both disorder-specific and transdiagnostic
interventions to prevent and treat currently unexplored and underexplored effects of suicide on loss survivors.
The cohort also can serve as an enduring resource for future research on suicide loss. Going forward, results
can be replicated across other populations (e.g., smaller US samples) to further contextualize our findings.
