INTRODUCTION
Post-Traumatic Stress Disorder (PTSD) is a serious public health issue that affects approximately 11% of the general population in Brazil1. It can arise as a response to direct or indirect exposure to a traumatic stressor event2,3. Individuals diagnosed with PTSD may exhibit reduced emotional regulation capacity and symptoms such as diminished interest in pleasurable activities, irritability, increased aggressiveness, violent behavior, and a persistent sense of threat. They are also at increased risk of comorbidities such as depression, substance abuse, and other disorders, which negatively impact quality of life and lead to higher costs for public health and social assistance systems2,4,5.
It is known that about 40 to 90% of the general population may be exposed to one or more traumatic stressor events during their lifetime, yet only about 20 to 30% go on to develop PTSD. Recent studies have focused on understanding why some individuals develop PTSD following exposure to a stressor event, while others who have experienced similar events do not4,6.
Public safety professionals, such as federal police officers, civil police officers, highway patrol officers, military police officers, and firefighters, are frequently exposed to traumatic and stressful events and are at high risk of developing PTSD7,8. Around 14% of police officers worldwide meet the diagnostic threshold for PTSD, which can negatively affect both their quality of life and occupational performance, leading to impaired job performance, increased work absences, or even career abandonment9,10. Additionally, they may experience cognitive impairments, memory and concentration difficulties, mood changes, depression, anxiety, and even suicidal ideation9.
Age, marital status, education level, work schedule, organizational hierarchy, pre-existing mental health conditions (such as anxiety and depression), and social support have been described in the literature as risk factors for PTSD among public safety professionals12,13.
Thus, PTSD has a significant impact on mental health, particularly among public safety professionals. However, there is still limited knowledge about the prevalence of this disorder and the determining factors that contribute to its development in this population. Understanding these aspects is essential to support the formulation of public policies and the implementation of effective mental health programs, as well as to guide the creation of more targeted prevention and intervention strategies. Therefore, this study aimed to assess the prevalence of PTSD and identify the factors associated with its development among public safety professionals.
METHODS
Study Design
This is a cross-sectional study conducted as part of the program entitled “SOMA-SI,” focused on research in the field of public security.
Study Location and Period
The study was carried out in the state of Espírito Santo, Brazil. Questionnaire application and data collection took place between April and December 2022.
Study Population and Eligibility Criteria
The study involved 206 public security professionals from the state of Espírito Santo, Brazil (Military Police, Federal Highway Police, Federal Police, Civil Guard, Military Fire Brigade, Civil Police, and Municipal Guard). Professionals were invited to voluntarily participate in the study.
All public security professionals from Espírito Santo who agreed to participate were included. The exclusion criterion was the presence of one or more missing responses in any of the 20 items of the PCL-5.
The sample size calculation was based on an estimated PTSD prevalence of 5% to 16% among police officers14,15, considering the population of 17,154 public security professionals in Espírito Santo in 2021, a 5% absolute precision, and a 95% confidence level. As a result, the minimum required sample size ranged from 73 to 205 public security professionals. Therefore, the obtained sample size (n = 206) provides adequate statistical power for the proposed multivariate analyses.
Data Collection
Data was collected in person. Socioeconomic data, lifestyle habits, and professional characteristics were gathered through semi-structured questionnaires. The public security agencies were categorized as: Military Police, Fire Brigade, and Others (Municipal Guard, Federal Police, and Federal Highway Police).
In addition, the nature of the work performed was recorded and classified as external service (field work; tasks carried out outside corporate facilities, such as patrolling, responding to incidents, rescue, or inspections) and Internal service (administrative, technical, or support tasks performed within the organizational units).
Psychological anamnesis was conducted in the presence of a psychology professional using the following instruments: WHOQOL-BREF to assess quality of life; Depression, Anxiety and Stress Scale‐21 (DASS-21), to assess symptoms of depression, anxiety, and stress; and Post-Traumatic Stress Disorder Checklist for DSM-5 (PCL-5) to assess symptoms indicative of probable PTSD.
The PTSD assessment was conducted using the PCL-5, a validated self-report instrument that evaluates the 20 PTSD symptoms outlined in the DSM-516. The PCL-5 can be used to assess the presence, intensity, and severity of PTSD symptoms in an individual’s life, track symptom changes during and after treatment, and support a provisional PTSD diagnosis. A cut-off score of ≥36 was used to identify participants with clinically significant symptoms, who were then categorized as having probable PTSD17, following the instrument’s guidelines for population screening without constituting a definitive diagnosis.
The WHOQOL-BREF stands as a validated and widely adopted instrument for evaluating quality of life18,19. It consists of a 24-item self-administered questionnaire covering four distinct domains: physical health, psychological health, social relationships, and environment18. In this study, participants’ quality of life was categorized as either better or worse, using domain-specific median scores derived from the sample as cut-off points20,21. The specific median cut-off scores were: physical health, 67.85; psychological health, 66.66; social relationships, 66.66; and environment, 59.37.
The 21-item Depression, Anxiety, and Stress Scale (DASS-21), a self-report instrument, was employed to assess symptoms of depression, anxiety, and emotional stress22,23. For statistical analysis, both continuous DASS-21 scores and categorical classifications derived from these scores were utilized. Based on symptom severity, participants were grouped into five levels: normal, mild, moderate, severe, and extremely severe for each respective domain.
Data Analysis
The normality of data distribution was assessed using the Shapiro-Wilk test, and appropriate statistical tests were selected based on the data distribution. Means (and standard deviations) or medians (and standard errors) were used for normally or non-normally distributed variables, respectively. PTSD prevalence was determined based on the frequency of participants who met the criteria for probable PTSD.
To investigate differences in PTSD scores between genders, the Wilcoxon-Mann-Whitney test was used, as it is suitable for comparing two independent samples without the assumption of normality. To assess differences in PTSD scores across age groups, the Kruskal-Wallis test was used, a non-parametric alternative to one-way ANOVA. If statistically significant differences were found, a Dunn post-hoc test with Bonferroni-adjusted p-values was applied to control for type I error.
Results were presented using descriptive measures (median and interquartile range), boxplot graphs, and test statistics and p-values for each comparison. All statistical analyses and graph construction were performed using R software (R Core Team, 2023)24, version 4.4.2, and the integrated development environment RStudio (Posit Team, 2023), version 2024.12.0. The chi-square test and Poisson regression with robust variance were used to examine factors associated with PTSD in the study population. These analyses were conducted using SPSS v.25 and STATA v.17, respectively. All tests used a 95% confidence interval and a significance level of 5% (p < 0.05).
RESULTS
This study included 206 public safety professionals, with a median age of 39 years and a median per capita income of R$2962.50, equivalent to $574.12. Most participants were male (73.8%), had children (73.8%), held a higher education degree (80.1%), worked in the Military Police (62.6%) and in internal service roles (59.2%), did not consume alcohol (56.3%), and did not smoke (91.3%). A majority reported better quality of life in the physical (56.3%), psychological (54.9%), social (56.4%), and environmental (56.1%) domains, and had symptoms classified as normal for depression (51.46%), anxiety (62.14%), and stress (53.4%). Among the 206 participants, 77 (37.4%) scored 36 or higher on the PCL-5, indicating probable PTSD (Table 1).
Table 1 : Sociodemographic characteristics, quality of life and lifestyle, and mental health condition of the sample (n=206) - public security professionals, stratified by the presence of probable PTSD.
| Characteristics | General | Without PTSD | PTSD | P valor |
|---|---|---|---|---|
| Sociodemographic | ||||
| Age, median (IQR) | 39 (13) years | |||
| Per capita income, median (IQR) | R$2962.50 (R$2700.00) | |||
| Sex, n (%) | 0.010* | |||
| Female | 54 (26.2) | 26 (48.1) | 28 (51.9) | |
| Male | 152 (73.8) | 103 (67.8) | 49 (32.2) | |
| Educational level, n (%) | 0.092 | |||
| Without higher education | 41 (19.9) | 21 (51.2) | 20 (48.8) | |
| With higher education | 165 (80.1) | 108 (65.5) | 57 (34.5) | |
| Workplace agency, n (%) | ||||
| Military police | 129 (62.6) | 67 (51.9) | 62 (48.1) | > 0.0001* |
| Fire department | 25 (12.1) | 21 (84.0) | 4 (16.0) | 0.016 |
| Others | 52 (25.2) | 41 (78.8) | 11 (21.2) | 0.005 |
| Type of service, n (%) | 0.075 | |||
| Field service (street) | 82 (39.8) | 45 (54.9) | 37 (45.1) | |
| Internal service | 122 (59.2) | 82 (67.2) | 40 (32.8) | |
| Children, n (%) | 0.178 | |||
| No | 53 (25.7) | 29 (54.7) | 24 (45.3) | |
| Yes | 152 (73.8) | 99 (65.1) | 53 (34.9) | |
| Quality of Life (WHOQOL) and Lifestyle Habits | ||||
| Alcohol consumption, n (%) | 0.206 | |||
| Does not currently drink | 90 (43.7) | 52 (57.8) | 38 (42.2) | |
| Currently drinks | 116 (56.3) | 77 (66.4) | 39 (33.6) | |
| Tobacco use, n (%) | 0.517 | |||
| Does not currently smoke | 188 (91.3) | 119 (63.3) | 69 (36.7) | |
| Currently smokes | 18 (8.7) | 10 (55.6) | 8 (44.4) | |
| Physical activity, n (%) | 0.870 | |||
| Sedentary | 71 (34.5) | 45 (63.4) | 26 (36.6) | |
| Active | 135 (65.5) | 84 (62.2) | 51 (37.8) | |
| Physical domain, n (%) | > 0.0001* | |||
| Worse quality of life | 90 (43.7) | 43 (47.8) | 47 (52.2) | |
| Better quality of life | 116 (56.3) | 86 (74.1) | 30 (25.9) | |
| Psychological domain, n (%) | > 0.0001* | |||
| Worse quality of life | 93 (45.1) | 40 (43.0) | 53 (57.0) | |
| Better quality of life | 113 (54.9) | 89 (78.8) | 24 (21.2) | |
| Social relationships domain, n (%) | > 0.0001* | |||
| Worse quality of life | 93 (45.4) | 41 (44.1) | 52 (55.9) | |
| Better quality of life | 112 (54.6) | 87 (77.7) | 25 (22.3) | |
| Environmental domain, n (%) | > 0.0001* | |||
| Worse quality of life | 90 (43.9) | 42 (46.7) | 48 (53.3) | |
| Better quality of life | 115 (56.1) | 86 (74.8) | 29 (25.2) | |
| Mental Health Conditions Depressive symptoms, n (%) | ||||
| Normal | 106 (51.46) | 93 (87.7) | 13 (12.3) | > 0.0001* |
| Mild | 28 (13.59) | 16 (57.1) | 12 (42.9) | 0.548 |
| Moderate | 31 (15.05) | 16 (51.6) | 15 (48.4) | 0.161 |
| Severe | 17 (8.25) | 1 (5.9) | 16 (94.1) | > 0.0001* |
| Extremely Severe | 24 (11.65) | 3 (12.5) | 21 (87.5) | > 0.0001* |
| Anxiety, n (%) | ||||
| Normal | 128 (62.14) | 106 (82.8) | 22 (17.2) | > 0.0001* |
| Mild | 10 (4.85) | 6 (60.0) | 4 (40.0) | 0.841 |
| Moderate | 26 (12.62) | 12 (46.2) | 14 (53.8) | 0.057 |
| Severe | 15 (7.28) | 2 (13.3) | 13 (86.7) | > 0.0001* |
| Extremely Severe | 27 (13.11) | 3 (11.1) | 24 (88.9) | > 0.0001* |
| Stress, n (%) | ||||
| Normal | 109 (53.4) | 96 (88.1) | 13 (11.9) | > 0.0001* |
| Mild | 27 (13.2) | 16 (59.3) | 11 (40.7) | 0.764 |
| Moderate | 28 (13.7) | 9 (32.1) | 19 (67.9) | 0.0004* |
| Severe | 27 (13.2) | 6 (22.2) | 21 (77.8) | > 0.0001* |
| Extremely Severe | 13 (6.4) | 0 | 13 (100) | > 0.0001* |
Source: Written by the author *Statistically significant difference (p < 0.05).
Figure 1 shows the distribution of PTSD scores between men and women. Wilcoxon-Mann-Whitney test found a significant difference in PTSD symptoms intensity between the two groups (W = 4994, p = 0.018). Females had a higher score median than the males, indicating that women exhibit higher levels of PTSD symptoms.

Figure 1 : Distribution of PTSD symptom severity scores between men and women. Source: Written by the author
Figure 2 presents the distribution of PTSD scores among different age groups, analyzed using the Kruskal-Wallis. The analyses of the age group influence in PTSD scores revealed significant differences (χ2 (4) = 27.23, p < 0.0001). The results showed that individuals aged between 30 and 39 years presented significantly higher PTSD scores than those aged between 40 and 49 years old (p = 0.008), 50 to 59 years old (p < 0.001) and ≥ 60 years old (p = 0.035). Other age group comparisons didn’t show statistically significant differences after correction for multiple comparisons.
Table 2 shows that determining sociodemographic factors for PTSD in the sample were age and sex. The analyses indicated that each added year in age was associated with a 3.3% lower prevalence of probable PTSD (p=0.009). The male sex was associated with the reduction of approximately 42% of PTSD prevalence (p=0.006).
Table 2 : Multivariate Poisson regression model with robust variance of sociodemographic factors associated with PTSD in public safety professionals.
| PTSD Status | ||
|---|---|---|
| Variables | PR (95% CI) | P value |
| Age | 0.97 (0.94 - 0.99) | 0.009 |
| Sex | 0.58 (0.39 - 0.85) | 0.006 |
| Per Capita Income | 1.0 (0.99 - 1.00) | 0.177 |
| Education Level | 0.72 (0.46 - 1.09) | 0.122 |
Source: Written by the author *Prevalence Ratio; 95% CI: 95% confidence interval. P-value 5% significance.
The Kruskal-Wallis test shows that 30–39 age group differs significantly from the 40–49 age group (p = 0.008), the 50–59 age group (p < 0.001), and the ≥60 age group (p = 0.035). PTSD: Post-Traumatic Stress Disorder.
The second model analyzed quality of life and lifestyle. The first being the determining factor for PTSD. For each one-unit increase in the quality of life score among public safety professionals in the psychological (p = 0.001) and environmental (p = 0.028) health domains, there was an associated decrease in PTSD prevalence by 2.35% and 1.69%, respectively (Table 3).
Table 3 : Multivariate analysis model of lifestyle and quality of life factors associated with PTSD in public safety professionals.
| PTSD Status | ||
|---|---|---|
| Variables | PR (95% CI) | P value |
| Tobacco use | 0.92 (0.49 - 1.72) | 0.802 |
| Alcohol consumption | 0.98 (0.69 - 1.38) | 0.931 |
| Physical activity | 1.36 (0.95 - 1.93) | 0.088 |
| Physical health domain | 1.00 (0.98 - 1.01) | 0.767 |
| Psychological health domain | 0.98 (0.96 - 0.99) | 0.001 |
| Social relationships domain | 1.00 (0.98 - 1.00) | 0.692 |
| Environmental health domain | 0.98 (0.96 - 0.99) | 0.028 |
Source: PR: Prevalence Ratio; 95% CI: 95% confidence interval. P-value for multivariate Poisson regression with robust variance at 5% significance.
The third multivariate model analyzed mental health condition factors, identifying stress as the determining factor for PTSD. Each one-point increase in the stress score (DASS-21 scale) was associated with a 6% higher prevalence of probable PTSD among public safety professionals.
DISCUSSION
Public safety professionals constitute a high-risk population for the development of mental health disorders due to the high-pressure work environment and exposure to traumatic events25,26. This study assessed the prevalence of Post-Traumatic Stress Disorder (PTSD) and its associated factors in a sample of 206 public safety professionals.
Our results revealed a high prevalence of PTSD and showed that while higher stress symptom intensity and being female were strongly associated with greater PTSD prevalence, factors such as older age and better quality of life in the psychological and environmental domains were associated with lower prevalence, outlining a multifactorial profile of vulnerability and protection in this population.
A high prevalence of probable PTSD was observed (37.4%), which exceeded the rates previously reported for the general population (1.3% to 12.2%)27, even within this at-risk group. The global estimate of PTSD in police officers is 14.4%28. A global cohort study reported that PTSD prevalence in firefighters ranged from 6.5% to 37.8%12. Studies conducted with Brazilian public safety professionals show PTSD prevalence ranging from 8.9% to 26.7% among police officers14,29 and from 6.9% to 24.4% among firefighters30,31.
This quantitative disparity underscores the severity of the mental health condition within the specific population of this study and substantiates an in-depth investigation of its determining factors. Furthermore, variability in PTSD prevalence rates among studies may be influenced by methodological differences, varying contexts, diagnostic criteria, cut-off points in assessment tools, and specific characteristics of the studied samples.
This study’s findings identified stress intensity as the strongest associated factor, where increased stress intensity was linked to higher prevalence of PTSD symptoms. This result aligns with other studies that have demonstrated stress as a risk factor in the development and worsening of PTSD severity32, suggesting that stress plays a central role in exacerbating and maintaining post-traumatic symptoms in this population. The DASS-21 is a tool that assesses emotional states of stress, including manifestations such as perceived tension, irritability, difficulty relaxing, and emotional overload33.
The association found between stress intensity and probable PTSD prevalence in our sample is consistent with the neurobiological literature. Public safety professionals are more exposed to conflict situations, trauma, and chronic stress34,35. Chronic stress is known to alter regulation of the HPA axis (Hypothalamic–Pituitary–Adrenal axis), leading to dysfunction that impairs stress response and adaptation. Studies have shown that PTSD is associated with HPA axis dysfunction, hyperreactivity of the amygdala, poor regulation of the prefrontal cortex, and autonomic nervous system imbalance leading to heightened fear responses, impaired emotional regulation, and reduced stress resilience36.
The results also showed a higher prevalence and intensity of probable PTSD in female public safety professionals, with being male associated with a 42% lower prevalence. This finding is consistent with substantial evidence from the general population, where a greater susceptibility to PTSD among women has been well-documented. This vulnerability is potentially mediated by a combination of factors, including differences in neurobiological responses to stress and higher exposure rates to specific types of institutional and interpersonal stress41.
Although studies with public safety professionals often do not show significant gender differences in PTSD prevalence, other studies do support our findings. A study with military police officers in Brazil showed that women and lower-ranking officers are more vulnerable to PTSD29. Obuobi-Donkor et al.12 also suggested that being female is a determining factor for PTSD. Similarly, Van der Meer et al.42showed that female police officers experienced more PTSD symptoms, and with greater severity, in a sample of officers seeking treatment for trauma-related symptoms. Furthermore, the male problem-focused coping mechanism is regarded as a protective factor for PTSD43.
The greater prevalence of PTSD in women is attributed to a significant biological basis, primarily involving the differential effects of gonadal hormones in the modulation of both the physiological stress axis and cognitive fear-extinction pathways. The dysfunctional stress response system that is often exhibited in cases of PTSD is significantly modulated by estrogens, which contributes to a heightened HPA axis reactivity that is observed in females. These hormones also influence the brain’s fear circuitry. The risk of developing PTSD or symptom exacerbation in women is highest during periods of low estrogen, such as specific phases of the menstrual cycle, puberty, the postpartum period, and the menopausal transition43,44.
The higher PTSD prevalence observed in women may not reflect intrinsic vulnerability but rather the consequence of a cumulative burden from both operational and gender-specific institutional stressors. Women are more frequently exposed to specific traumatic events, including assault, moral and sexual harassment, workplace hostility, and discrimination29,41,42,45. Therefore, this finding suggests that effective prevention policies must address trauma management and combat institutional challenges, such as gender-based harassment and discrimination.
The Poisson multivariate regression indicated that each additional year of age was associated with a 3.3% lower prevalence of probable PTSD. Literature data confirm a higher prevalence of PTSD among younger individuals48,49. Analyses of populations with chronic exposure to trauma, such as the group of war veterans examined by Richardson et al.50and Konnert and Wong51have shown that PTSD severity is associated with younger age among war veterans and lower levels of PTSD symptoms among older war veterans, supporting our results.
This possible protective effect may be explained by the fact that older adults tend to cope more positively with adversity, have greater adaptive capacity, and better cognitive reappraisal skills52. Yuan et al.13suggested that, with time and experience, professionals accumulate a more effective repertoire of coping strategies, making them more resilient to new traumatic events. Furthermore, the possibility of individuals with greater susceptibility to PTSD do not remain in the profession long-term due and there are a selection process that concentrates the most resilient individuals.
Despite awareness of the risk, epidemiological data on PTSD prevalence and its interaction with multiple quality-of-life domains among public safety professionals in Brazil are scarce, specifically in the state of Espírito Santo. This study fills that gap and shows that better quality of life in the psychological and environmental domains reduces PTSD prevalence by 2.35% and 1.69%, respectively. Studies show that PTSD symptom severity is bidirectionally associated with worse quality of life across all domains, especially in social functioning, mental health, and physical well-being53, and that improvements in quality of life are associated with reduced PTSD symptoms56,57, corroborating our findings.
The environmental domain of the WHOQOL-BREF considers factors such as physical safety and sense of protection, the quality of the physical and social environment (e.g., noise, pollution, traffic, and climate), and access to important resources (e.g., financial means, health services, transportation) and how these affect overall quality of life58,59. The psychological domain includes aspects such as psychological distress, depression, anxiety, self-esteem, sense of purpose, spirituality, memory and concentration, and perceived control and autonomy60. Studies have shown that job- and organization-related stress, the constant need for vigilance, exposure to potentially traumatic events, and sleep deprivation due to shift work negatively impact the psychological quality of life in public safety professionals61,62.
Simultaneously analyzing quality-of-life domains in this population is extremely important because it reveals how stress correlates with perceptions of psychological and environmental quality of life. Quality of life has been widely studied by researchers, particularly for its potential impact in various life domains. Enhancing quality of life may represent a preventive and therapeutic strategy for treating mental disorders such as depression, anxiety, schizophrenia, and PTSD56,63.
Some studies suggest that mindfulness-based interventions, stress management, and emotional intelligence training can improve quality-of-life perceptions and play a significant role in reducing PTSD symptoms66,67.
This study has many limitations. The cross-sectional design does not allow for establishing causal relationships between determining factors and PTSD. It is also important to note that the screening questionnaire used is not a diagnostic tool, which is why the term “probable PTSD” is used. Future studies should employ longitudinal designs and collect data through semi-structured interviews.
CONCLUSION
Our results highlight the high prevalence of PTSD in the population of public security professionals and the association between emotional stress perception, the psychological and environmental domains of quality of life, and PTSD, as well as other intrinsic factors such as age and sex.
These findings reinforce the importance of developing public mental health policies aimed at public safety professionals, especially younger individuals and women. We suggest that such policies focus primarily on well-being, stress management, and early screening and diagnosis of mental disorders, and that they contribute to improving occupational and psychological quality of life, reducing stress, and preventing or supporting the recovery from PTSD in public safety professionals.
Table 4 : Multivariate analysis model of mental health conditions among public safety professionals.
| PTSD Status | ||
|---|---|---|
| Variables | PR (95% CI) | P value |
| Depression | 1.02 (0.99 - 1.03) | 0.118 |
| Anxiety | 1.00 (0.98 - 1.02) | 0.712 |
| Stress | 1.06 (1.03 - 1.08) | >0.0001 |
Source: PR: Prevalence Ratio; 95% CI: 95% confidence interval. P-value for multivariate Poisson regression with robust variance at 5% significance.















