Firefighters are chronically exposed to various traumatic experiences throughout their career. Thus, firefighters are a population with heightened susceptibility to posttraumatic stress disorder (PTSD), and some studies have suggested that depression and alcohol use disorders (AUDs) are also possible sequelae of trauma exposure (Bonde et al., 2016). In addition, daily stressors, shifting work schedules, and frequent night duties may lead to the disruption of the normal circadian rhythm and fragmented sleep (Savall et al., 2021; Wolkow et al., 2019).

Most studies on firefighters have focused on examining cases of PTSD; however, evidence has demonstrated that PTSD rarely occur alone in firefighters exposed to traumatic events (Jitnarin et al., 2022). High comorbidity rates have been repeatedly reported in military and veteran populations, who are routinely exposed to trauma during their jobs (Stander et al., 2014). A meta-analysis of 57 studies reported that 52 % of adults with PTSD had a concurrent diagnosis of major depressive disorder (MDD) (Rytwinski et al., 2013), whereas another study found that 97.4 % of veterans diagnosed with PTSD fulfilled criteria for other mental disorders (Klaric et al., 2017). Individuals struggling with PTSD symptoms may feel incompetent and depressed as a result of failed attempts to mitigate PTSD and anxiety symptoms (Mangelli et al., 2005). Alcohol consumption often increases in an attempt to manage with PTSD symptoms (Kelley et al., 2013) like irritability, concentration problems, and hyperarousal, leading to an increased risk for the development of AUDs. Individuals may avoid sleep to escape trauma-related nightmares, which may lead to increased arousal and poor sleep quality (van Wyk et al., 2016).

Despite the suggested high occurrence of comorbidities, the rate and patterns of comorbidities have not been well investigated in firefighters. Latent profile analysis (LPA) classifies individuals into distinct subgroups based on inter-individual variations in different components of variables (Li et al., 2020; Marsh et al., 2009). Therefore, individuals are divided into latent subclasses based on item response patterns (Nugent et al., 2012), such that the people within a subgroup show similar responses, but their responses differ from those of other subgroups (Contractor and Weiss, 2019). Identification of subgroups of PTSD symptoms with co-occuring depression, AUDs, and insomnia may shed insights on comorbidity patterns, prognosis, and trajectories of firefighters (Griffith et al., 2022). As comorbidity can influence treatment outcomes, the identification of subgroups based on their co-occurrence pattern may assist in the development of better treatment programs.

The present study aimed to examine the classification of subgroups (heterogeneous latent classes) based on PTSD, depression, AUDs, and insomnia symptoms using data obtained from a national sample of firefighters. The purpose of this study was 1) to identify the optimal latent class number for this population of firefighters based on endorsed PTSD, depression, AUD, and insomnia symptoms, and (2) to investigate the association of best-fitting class membership and clinically important factors, such as reactions of anger, resilience, and the number of traumatic experiences.