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INTRODUCTION
Contemporary global dynamics reflect profound transformations in demographic, nutritional, urban, and socioeconomic patterns. This complex interconnection is redefining the contours of lifestyle in many societies, triggering multifaceted transitions. The interaction between demographic and nutritional transitions, along with the urbanization process and socioeconomic growth, is promoting a way of life marked by a vigorous routine1. This pattern is often identified by the predominant consumption of processed foods, whose nutritional value is reduced while the caloric content remains high. This scenario has played a significant role in increasing the prevalence of Chronic noncommunicable diseases (NCDs), notably obesity2.
By exploring the interconnections of these factors, the impact of this sociodemographic evolution on public health becomes evident3. Simultaneously, sociocultural transformations have increased stress levels in the general population4,5, generating significant impacts on health systems around the world.
Stress, as outlined by Selye’s three-phase model6, presents a relevant dimension to this discussion. The body’s reaction to the intensification of routine and modern challenges manifests itself in distinct phases, from the alert phase, with the release of adrenaline and noradrenaline, to the resistance phase, characterized by the body’s adaptation through the release of cortisol. However, the exhaustion phase highlights the organism’s vulnerability, suggesting a potential link between contemporary sociodemographic challenges and susceptibility to psychosocial stress. Understanding these interconnections amplifies the perception of the multiple impacts on health, opening space for more comprehensive preventive strategies.
This definition is defended by Lipp7 as a state of tension that interrupts the normal functioning of the body in response to stressful events, such as changes in employment, violence, family losses, financial instability, and illnesses6,8,9. It utilizes the model defined by Selye6 in the instrument for evaluating these symptoms in adults10.
In this context, public security professionals, due to the challenging nature of the activities they perform, constantly face risks and dangerous situations11. Studies in Brazil have revealed elevated levels of stress in this group, with a prevalence of around 40%12,13, showing a direct relationship between police activity and chronic stress14,15.
The negative influence of stress on the role performed by public security agents, whether due to absences for psychiatric treatments or reduced productivity, not only impacts the costs of the health system but also compromises the effectiveness of public security operations16,17.
Excessive exposure to stress, with individuals mainly in the exhaustion phase, can lead to metabolic problems, such as hyperglycemia, insulin resistance, dyslipidemia18, and be associated with the accumulation of fat in the central region of the abdomen due to changes in hormonal regulation, which occur due to excessive exposure to stress, such as sensitivity to ghrelin or even a reduction in its production, due to impairment of the hypothalamic-pituitary-adrenal (HPA) axis19.
In addition, excess cortisol can negatively affect the beta cells of the pancreas, increasing the production of glucose in the liver and body, contributing to insulin resistance, and may even lead to the development of type 2 diabetes, in addition to other metabolic problems20. In this sense, there is a prominent need for studies that address the relationship between stress, nutritional status, and the respective consequences in public security professionals, especially in the context of the state of Espírito Santo, aiming to support preventive strategies and interventions aimed at promoting the health of these professionals and optimizing performance in public security activities.
The scarcity of studies that address the nutritional status of these professionals, considered a risk factor for the development of NCDs21, represents a gap in the scientific literature. The association of obesity with several other NCDs, which are responsible for a large number of deaths worldwide, regardless of socioeconomic level22, reinforces the urgency of investigations that address this relationship. Therefore, the specific characterization of stress among public security professionals, especially in the state of Espírito Santo, still requires in-depth analysis.
Therefore, the objective was to evaluate abdominal obesity and its association with stress symptoms in public security professionals in the metropolitan region of a Brazilian capital.
METHODS
Study design, location, and period
This is a cross-sectional study that is part of the larger study entitled “SOMA-SI - A Well-Being Self-Management Program based on Stress Analysis of Public Security Agents in Espírito Santo”. Data were collected from April to December 2022.
Sample and eligibility criteria
The sample was made up of public security agents from the metropolitan area of Vitória, Espírito Santo, including the Federal Police, Federal Highway Police, Military Police, Military Fire Brigade, Municipal Guard of Vitória, Serra, Viana and Vila Velha.
The sample size was calculated considering the sample of public security personnel in the State of Espírito Santo, whose population in 2021 corresponded to 3,723 individuals, 2,547 Military Police, 649 Military Firefighters, 247 Federal Police and 280 Municipal Guards. The sample size was calculated by setting α at 5% (type I error) and considering a statistical power of 80% (β=0.20). In the calculation was taken into account the prevalence of obesity in the state, 17.9%, evidenced in the last Vigitel - a telephone survey carried out annually by the Brazilian Ministry of Health23, in which the sample of this research was equal to 216 public security agents.
Inclusion criteria were: adults > 18 years of age of both sexes; public security agents and residents of the State of Espírito Santo; police officers belonging to the security forces at the State, Federal and Municipal levels, active in their role. The following were excluded from this study: public security officers who were temporarily or permanently absent from police activities during the study; diagnosed with a mood or psychiatric disorder or undergoing psychiatric treatment.
Data collection
Blood pressure
Blood pressure was measured according to the method validated by Mill24 in the ELSA Brazil study, with the subjects resting for 5-10 minutes, in a sitting position with the feet supported on the floor and, after emptying the bladder, with a cuff suitable for the circumference of the arm. The first recorded measurement was discarded, and after two more measurements, 1 minute apart, if the difference was greater than 5 mmHg, a third measurement was taken and the arithmetic mean of the last two measurements was calculated24.
Anthropometric assessment
The anthropometric assessment was performed by nutritionists in the morning, respecting the minimum fasting period of 8 hours. Participants were instructed to fast for at least 8 hours, not to consume caffeine or exercise in the 24 hours prior to the examination, and to remove metal objects such as earrings, rings, and glasses.
Height was assessed using a stadiometer with a maximum capacity of 2.10 m and an accuracy of 0.5 cm. Waist circumference was measured using an inelastic tape measure with an accuracy of 0.1 cm and a maximum length of 2 m. It was classified according to the reference25performed at the midpoint between the last rib and the iliac crest26,27. Hip circumference was measured at the point of greatest volume in the trochanteric region26. Body mass index (BMI) was calculated and classified according to the WHO reference for adults25, with underweight individuals presenting BMI values of 18.5 kg/m2, eutrophic: 18.5 to 24.9 kg/m2, overweight: 25.0 to 29.9 kg/m2, and obese: BMI≥ 30 kg/m2, which is later categorized into two variables, BMI: not overweight: 18.5 kg/m2 to 24.9kg/m2, overweight: >25kg/m2.
Stress Symptom Inventory
The Lipp’s Inventory of Stress Symptoms for adults (LSSI) is an instrument validated in the Brazilian adolescent and adult population with a Cronbach’s alpha of 0.9110.
This inventory was standardized and validated by Lipp and Guevara7 and is based on a three-phase model developed by Selye6. The phases of stress included in the LSSI are alert, resistance, and exhaustion. The inventory also contains a total of 53 closed-ended questions, divided into three dimensions that deal with physical (34 items) and psychological (19 items) symptoms.
Data analysis
The data were tabulated in a Microsoft Excel spreadsheet and subjected to a prior consistency analysis. In order to characterize the sample in terms of socio-demographic, health and lifestyle profile, it was decided to present the categorized variables, with the results expressed in relative and absolute frequencies. For data analysis, the chi-square test was used, with categorical variables, those that were continuous were categorized as dichotomous, and then the chi-square test was used at 5% significance. To compare the difference in the medians of the waist circumference factor scores between groups of individuals without symptoms or with symptoms of stress, the Mann-Whittney test was chosen at 5% significance. The Statistical Package for Social Science version 25.0 for Windows® (SPSS) was used for all statistical analyses, with alpha set at 5%. The option of not including missing data in the tests was used.
Ethical and legal aspects of research
The study was approved by the Research Ethics Committee of the Health Sciences Center at the Federal University of Espírito Santo (CEP-CCS-UFES), according to the Certificate of Ethical Appreciation no. 53145521.1.0000.50.60, in compliance with Resolution 466/2012 of the Brazilian National Health Council and approval no. 5.163.467.
RESULTS
The total sample consisted of 216 participants, of whom 75.5% were male and 24.5% were female, with the majority identifying as non-white (63.7%). Most individuals reported working for 15 years or more (61.6%), earning less than five minimum wages (81.1%), and having a college education (77.3%). The largest percentages of the sample worked in the military police (67.6%), had children (72.2%), consumed alcoholic beverages (57.9%), did not currently smoke (9.3%), were in the normal waist circumference risk class (56.9%), and were overweight by BMI (77.3%) (table 1).
Table 1 : Sociodemographic characteristics and anthropometric measurements of public security agents in Grande Vitória
| Characteristics | Total n (%) | Female n(%) | Male n(%) | p-value |
|---|---|---|---|---|
| Race/color | ||||
| White | 78(36.11) | 19 (24.4%) | 59 (75.6%) | 0.940 |
| Non-white | 137(63.43) | 34 (23.8%) | 103 (75.2%) | |
| No information | 1(0.46) | |||
| Working time (years) | ||||
| ≥ 15 | 133(61.6) | 31 (23.3%) | 102 (76.7%) | 0.595 |
| 0 - 15 | 83(38.4) | 22 (26.5%) | 61 (73.5%) | |
| Income (minimum wages) | ||||
| ≤ 5 | 150(69.44) | 35 (23.3%) | 115 (76.7%) | 0.318 |
| ≥6 | 35(16.20) | 11 (31.4%) | 24 (68.6%) | |
| No information | 31(14.35) | |||
| Education | ||||
| Secondary or technical | 49(22.7) | 8 (16.3%) | 41 (83.7%) | 0.129 |
| Bachelor's degree | 167(77.3) | 45 (26.9%) | 122 (73.1%) | |
| Field of operation | ||||
| Military police | 146(67.6) | 31 (21.2%) | 115 (78.8%) | 0.059a |
| Municipal guard | 23(10.6) | 7 (30.4%) | 16 (69.6%) | |
| Federal police | 19(8,8) | 9 (47.4%) | 10 (52.6%) | |
| Fire department | 21(9.7) | 3 (14.3%) | 18 (85.7%) | |
| State Secretariat for Public Security (SESP) | 7(3.2) | 3 (42.9%) | 4 (57.1%) | |
| Drinking habit | ||||
| Does not currently drink | 91(42.1) | 24 (26.4%) | 67 (73.6%) | |
| Currently drinks | 125(57.9) | 29 (23.2%) | 96 (76.8%) | 0.593 |
| Tobacco | ||||
| Do not smoke | 195(90.28) | 50 (25.6%) | 145 (74.4%) | 0.293a |
| Currently smokes | 20(9.26) | 3 (15.0%) | 17 (85.0%) | |
| No information | 1(0.46) | |||
| Waist circumference | ||||
| Normal risk | 123(56.9) | 31 (25.2%) | 92 (74.8%) | 0.794 |
| Increased risk | 93(43.1) | 22 (23.7%) | 71 (76.3%) | |
| BMI | ||||
| Normal | 49(22.7) | 13 (26.5%) | 36 (73.5%) | 0.712 |
| Overweight | 167(77.3) | 40 (24.0%) | 127 (76.0%) | |
| Stress phase | ||||
| None | 77(35.6) | 15 (19.5%) | 62 (80.5%) | |
| Alert | 1(0.5) | 0 (0.0%) | 1 (100.0%) | |
| Resistance | 92(42.6) | 22 (23.9%) | 70 (76.1%) | 0.279a,b |
| Near exhaustion | 16(7.4) | 7 (43.8%) | 9 (56.3%) | |
| Exhaustion | 30(13.9) | 9 (30.0%) | 21 (70.0%) | |
| Blood pressure | ||||
| Normal | 124(57.41) | 42 (33.9%) | 82 (66.1%) | |
| Altered | 91(42.13) | 11 (12.1%) | 80 (87.9%) | <0.001 |
| No information | 1(0.46) | |||
| Fasting blood glucose | ||||
| Desirable | 158 (73.15) | 44 (27.8%) | 114 (72.2%) | |
| Altered | 52 (24.07) | 7 (13.5%) | 45 (86.5%) | 0.036* |
| No information | 6(2.78) | |||
| Cholesterol | ||||
| Desirable | 107 (49.54) | 32 (29.9%) | 75 (70.1%) | |
| Altered | 106 (49.07) | 20 (18.9%) | 86 (81.1%) | 0.610 |
| No information | 3(1.39) | |||
| Triglycerides | ||||
| Desirable | 158(73.15) | 39 (24.7%) | 119 (75.3%) | |
| Altered | 55(25.46) | 13 (23.6%) | 42 (76.4%) | 0.876 |
| No information | 3(1.39) | |||
| HDL | ||||
| Desirable | 211(99.1) | 51 (24.2%) | 160 (75.8%) | |
| Altered | 2 (0.93) | 1 (50.0%) | 1 (50.0%) | 0.397a,b |
| No information | 3(1.39) | |||
| LDL | ||||
| Desirable | 104 (48.15) | 32 (30.8%) | 72 (69.2%) | |
| Altered | 105 (48.61) | 20 (19.0%) | 85 (81.0%) | 0.500 |
| No information | 7(3.24) |
Note: BMI: Body mass index, Bonferroni correction 5x2=10 = 0.05/10=0.005. No information: individuals who selected the “do not respond option.”
Table 2 presents the results of the association analysis between nutritional status and the classifications obtained in the LSSI. It is noted that statistically significant values were identified for stress symptoms (p = 0.004).
Table 2 : Chi-square test of association between abdominal obesity, sociodemographic variables, and stress phase classification according to the Lipp's Inventory of Stress Symptoms
| Waist Percentage | ||||
|---|---|---|---|---|
| Normal Risk | Increased Risk | |||
| Characteristics | Total n(%) | n(%) | n(%) | p-value |
| Sex | ||||
| Female | 53(24.5) | 31(58.5) | 22(41.5) | |
| Male | 163(75.5) | 42(53.8) | 36(46.2) | 0.794 |
| Race | ||||
| White | 78(36.3) | 42(53.8) | 36(46.2) | |
| Non-white | 137(63.7) | 80(58.4) | 57(41.6) | 0.518 |
| No information | 1(0.46) | |||
| Working time (years) | ||||
| ≥ 15 | 133(61.6) | 76(57.1) | 57(42.9) | |
| 0 - 15 | 83(38.4) | 47(56.6) | 36(43.4) | 0.941 |
| Income (minimum wages) | ||||
| ≤ 5 | 150(81.1) | 81(54.0) | 69(46.0) | |
| ≥6 | 35(19.9) | 21(60.0) | 14(40.0) | 0.520 |
| No information | 31(14.35) | |||
| Education | ||||
| Secondary or technical | 49(22.7) | 32(65.3) | 17(34.7) | |
| Bachelor's degree | 167(77.3) | 91(54.5) | 76(45.5) | 0.179 |
| Field of operation | ||||
| Military police | 146(67.6) | 81(55.5) | 65(44.5) | |
| Municipal guard | 23(10.6) | 15(65.2) | 8(34.8) | |
| Federal police | 19(8,8) | 14(73.7) | 5(26.3) | |
| Fire department | 21(9.7) | 10(47.6) | 11(52.4) | |
| State Secretariat for Public Security (SESP) | 7(3,2) | 3(42.9) | 4(57.1) | 0.373a |
| Drinking habit | ||||
| Does not currently drink | 91(42.1) | 49(53.8) | 42(46.2) | |
| Currently drinks | 125(57.9) | 74(59.2) | 51(40.8) | 0.616 |
| Tobacco | ||||
| Does not smoke | 195(90.28) | 112(57.4) | 83(42.6) | |
| Currently smokes | 20(9.26) | 11(55.0) | 9(45.0) | 0.834 |
| No information | 1(0.46) | |||
| BMI | ||||
| Normal | 49(22.7) | 47(95.9) | 2(4,1) | |
| Overweight | 167(77.3) | 76(45.5) | 91(54.5) | >0.001* |
| Stress phase | ||||
| None | 77(35.6) | 54(70.1) | 23(29.9) | |
| Alert | 1(0.5) | 0(0) | 1(100) | |
| Resistance | 92(42.6) | 49(53.1) | 43(46.7) | |
| Near exhaustion | 16(7.4) | 5(31.3) | 11(68.8) | |
| Exhaustion | 30(13.9) | 15(50) | 15(50) | 0.016a,*,c |
| Stress | ||||
| None | 77(35.5) | 54(70.1) | 23(29.9) | |
| At some stage | 139(64.5) | 69(49.6) | 70(50.4) | 0.004* |
| Blood pressure | ||||
| Normal | 124(57.41) | 76(61.3) | 48(38.7) | |
| Altered | 91(42.13) | 47(51.6) | 44(48.4) | 0.158 |
| No information | 1(0.46) | |||
| Fasting blood glucose | ||||
| Desirable | 158 (73.15) | 91(57.6) | 67(42.4) | |
| Altered | 52 (24.07) | 29(55.8) | 23(44.2) | 0.818 |
| No information | 6(2.78) | |||
| Cholesterol | ||||
| Desirable | 107 (49.54) | 56(52.3) | 51(47.7) | |
| Altered | 106 (49.07) | 66(62.3) | 40(37.7) | 0.143 |
| No information | 3(1.39) | |||
| Triglycerides | ||||
| Desirable | 158(73.15) | 92(58.2) | 66(41.8) | |
| Altered | 55(25.46) | 30(54.5) | 25(45.5) | 0.634 |
| No information | 3(1.39) | |||
| HDL | ||||
| Desirable | 211(99.1) | 120(56.9) | 91(43.1) | |
| Altered | 2 (0.93) | |||
| No information | 3(1.39) | 2(100.0) | 0(0,0) | ,220a,c |
| LDL | ||||
| Desirable | 104 (48.15) | 55(52.9) | 49(47.1) | |
| Altered | 105 (48.61) | 64(61.0) | 41(39.0) | 0.239 |
| No information | 7(3.24) | |||
Note: BMI: Body Mass Index. HDL: High Density Lipoprotein. LDL: Low Density Lipoprotein It is. No information: individuals who selected the “do not respond option.”
Figure 1 shows the result of the Mann-Whitney analysis of the relationship between abdominal adiposity and stress at any stage of the Lipp’s Inventory of Stress Symptoms.
DISCUSSION
The present study aimed to analyze the relationship between abdominal adiposity and stress symptoms in public safety professionals, following the criteria established by Lipp. A detailed analysis of the sample with respect to gender revealed significant associations with age group, length of service, type of service (internal/external), income, body mass index, and presence of children. However, there was no direct relationship between these variables and stress symptoms or anthropometric measures. However, a statistically significant correlation was found between abdominal circumference and stress in the sample.
In this context, it is important to emphasize that prolonged exposure to stress may be associated with the accumulation of fat in the central region of the abdomen, as found in this study. This result may be related to changes in hormonal regulation, affecting sensitivity to ghrelin and, in some cases, leading to a reduction in its production due to impairment of the hypothalamic-pituitary-adrenal (HPA) axis19. The association between prolonged stress and abdominal obesity has also been shown in other studies28,29. Therefore, this relationship is bidirectional, as stress can influence abdominal obesity and vice versa, creating a cycle that is potentially harmful to health30. This condition can lead to metabolic problems such as hyperglycemia, insulin resistance, and dyslipidemia18.
It is noteworthy that prolonged exposure to stress, and consequently cortisol, increases blood glucose levels and stimulates the maturation of adipocyte precursors, promoting excess body fat31. This increase in cortisol stimulates the brain’s mesolimbic reward pathways, resulting in increased intake of palatable, sugary foods32. A study of 3,000 participants found that individuals who were regularly exposed to stressful situations were more likely to develop obesity and type 2 diabetes than those with low exposure to stress33, supporting the findings of this study.
Although the present study did not find an association between fasting blood glucose levels and stress, it highlights the complex relationship between mental and physical health found in other studies in which blood glucose presented association with psychological stress9,32,34. However, the measurement of fasting blood glucose in public safety professionals may not be sensitive when we encounter individuals who are highly stressed and they took night shifts35.
The HPA is a major regulator of the hormones glucocorticoids, which play a fundamental role in glucose control during periods of acute stress36,37. Cortisol, the end product of the HPA, stimulates glucose production and glycogen depletion, in addition to reducing the uptake of glucose by peripheral tissues, thereby increasing its concentration in the bloodstream and leading to hyperglycemia38. Sustained activation of the HPA axis by stressful stimuli results in increased release of glucocorticoids, the major hormonal response to stress, which can disrupt normal glucose regulation39. Furthermore, constant activation of this axis has been found even in patients with type 2 diabetes40.
In conclusion, although this study did not find an association between stress and fasting glucose, the interaction between these factors is multifaceted and complex. Future studies that include additional variables and take into account the heterogeneity of the stress response and more robust analyses should be considered.
Another mechanism reported in research is that chronic stress can affect appetite-regulating hormones such as ghrelin and leptin. This influence can lead to a reduction in the feeling of satiety, causing changes in eating behavior, leading to the consumption of more palatable foods and contributing to the accumulation of abdominal fat19,41.
It is important to highlight the predominance of males among public safety personnel, which reflects a pattern observed in other studies of this population28,42. Having a relationship with blood glucose and blood pressure, in line with the literature that points out differences in the search for health services between men and women, indicating that men tend to seek health services less43-45, and when they do, they usually present the most advanced or critical state of the disease28.
However, there was a preponderance of overweight in the sample, which exceeded the population averages of the state, according to data from the last Vigitel23. This finding is consistent with recurring findings in research on security officers42,46,47. This is consistent with a high incidence of stress symptoms in the sample (63.4%), with a significant value in the exhaustion phase (13.9%), which exceeds values observed in other locations and may indicate a complex relationship between stress and obesity42,47.
Although the present study has a cross-sectional design, this does not allow precise causal relationships to be established. However, these findings and discussions are crucial for understanding the factors that contribute to the health of these professionals, as they can support intervention strategies and policies aimed at promoting the mental and physical health of this population.
Furthermore, there is a lack of studies on this topic, especially in Brazil, and the factors that may explain this gap are: the reluctance of some institutions and police officers to engage in interventions or research on mental health, the fear of police officers regarding the confidentiality of the data reported, the fear of demonstrating weakness in front of professional colleagues and the institution48,49. This also had an impact on this study as a limitation in which, among some variables, the option “I prefer not to answer” was highlighted by police officers.
It is also recommended that additional methods be used to more accurately assess the degree of influence that stress and abdominal obesity have on public safety officers.
CONCLUSION
The study revealed a higher frequency of abdominal obesity in public safety officers with higher levels of stress symptoms, in addition to demonstrating frequency high incidence of overweight in the sample, a high incidence of stress symptoms, indicating a complex and bidirectional relationship between both variables. In addition to confirming previous findings about the association between prolonged stress and abdominal obesity, the research identified correlations between blood glucose, blood pressure and demographic characteristics, such as sex and age.
