Empirical clustering to identify individuals for whom insomnia is more closely related to suicidal ideation

Background: Although the effect sizes are modest, insomnia is consistently associated with suicidal thoughts and behaviors. Subgroup analyses can efficiently identify for whom insomnia is most relevant to suicidal ideation. To improve clinical case identification, the present study sought to identify subclusters of lifetime suicidal ideators for whom insomnia was most closely related to current suicidal ideation. Methods: Data on N = 4750 lifetime suicidal ideators were extracted from the Military Suicide Research Consortium's Common Data Elements. Data on sociodemographic characteristics, severity and history of suicidal thoughts and behaviors, and related clinical characteristics were clustered by unsupervised machine learning algorithms. Robust Poisson regression estimated cluster by insomnia associations with current suicidal ideation. Results: Three clusters were identified: a modest symptom severity cluster (N = 1757, 37.0 %), an elevated severity cluster (N = 1444 30.4 %), and a high severity cluster (N = 1549 32.6 %). In Cluster 1, insomnia was associated with current suicidal ideation (PRR 1.29 [1.13–1.46]) and remained significant after adjusting for sociodemographic and clinical covariates. In Cluster 2, insomnia was associated with current suicidal ideation (PRR 1.14 [1.01–1.30]), but not after adjusting for sociodemographic and clinical covariates. In Cluster 3, insomnia was associated with current suicidal ideation (PRR 1.12 [1.03–1.21]) and remained significant after adjusting for sociodemographic covariates, but not clinical covariates. Limitations: Cross-sectional design, lack of diagnostic data, non-representative sample. Conclusion: Insomnia appears more closely related to current suicidal ideation among modest severity individuals than other subgroups. Future work should use prospective designs and more comprehensive risk factor measures to confirm these findings.