Abstract
Purpose
Police work is a stressful occupation. Depressive symptoms, which may occur as a result of exposure to stressors in police work, have been known to be associated with an increased risk of cardiovascular disease. This cross-sectional study investigated the association between depressive symptoms and carotid artery intima-media thickness (CIMT) among police officers.
Methods
CIMT was measured with B-mode carotid ultrasonography. Depressive symptoms were measured using the Center for Epidemiological Studies Depression (CES-D) scale. Analyses of variance and covariance were utilized to examine the mean values of common CIMT (CCA IMT) and maximum CIMT (MMXIMT) across quintiles of depressive symptoms.
Results
Participants included 412 officers (mean age = 41 years). Hypertension status significantly modified the association between CES-D score and CIMT. The association between CES-D score and CCA IMT was statistically significant (adjusted P = 0.030) but only among officers without hypertension. The associations between CES-D score and MMXIMT were not significant among officers with or without hypertension. Our results also showed that among officers who reported poor sleep quality, mean levels of CCA IMT, and MMXIMT tended to increase as depressive symptoms increased.
Conclusions
Depressive symptoms may be therefore be independently associated with CIMT, yet masked by hypertension. Even though sleep quality did not significantly modify the main association, our results also suggest that poor sleep quality may act synergistically with depressive symptoms to increase CIMT. Future prospective work would help to clarify these associations.
Keywords: Cardiovascular disease, Depression, Risk factors, Police
Introduction
Police work is considered a stressful occupation which not only involves danger and traumatic event exposure, but also organizational stressors such as lack of support, punishment-centered executive philosophies, and excessive paperwork (Violanti et al. 2006; Berg et al. 2005; Kop and Euwema 2001; Patterson 2003; Spielberger et al. 1982; Violanti and Aron 1994).
Depression may be one outcome of exposure to police work stressors and it has been associated with increased risk of cardiovascular disease (CVD) (Wang et al. 2010; Chen et al. 2006; Whipple et al. 2011). Barefoot and Schroll (1996) found that a high level of depressive symptoms predicted the subsequent occurrence of myocardial infarction and mortality in a 21-year follow-up study. Appels and Mulder (1988) found relationships between various negative psychological states and the occurrence of coronary heart disease (CHD). Depression has also been associated with biological outcomes which exacerbate the risk of CVD, including hyperactivity within the hypothalamic–pituitary–adrenal (HPA) axis, diminished heart rate variability, and ventricular instability (Musselman et al. 1998a, b).
Due to their occupational exposure and increased risk for depression, police officers may also be at higher risk for CVD (Violanti et al. 1998; Franke and Anderson 1994; Franke et al. 1998). Based on the previous research, we tested the hypothesis that depressive symptoms in police officers are associated with carotid artery intima-media thickness (CIMT) after adjustment for traditional CVD risk factors. Stewart et al. (2007) found that higher depressive symptoms at baseline were associated with greater 3-year change in carotid intima-media thickness even after taking into account demographic factors, cardiovascular risk factors, medication use, medical conditions, and other correlated negative emotions. Pizzi et al. (2010) found that IMT is higher in depressed subjects, indicating that atherosclerosis is accelerated in depressed patients. These authors contribute this to mechanisms which connect depression and coronary artery disease, such as inflammation and imbalance of the autonomic nervous system. Haas et al. (2005), adjusting for baseline cardiovascular risk factors, found participants with elevated depression scores at baseline were > 2 times as likely as those with no depressive symptoms to have carotid plaque. This study suggested that hypothalamic–pituitary–adrenal (HPA) dysregulation, diminished heart rate variability, altered blood platelet function, and noncompliance with medical treatments underlie the association between depression and cardiovascular disease. Conversely, Rice et al. (2009) in the Baltimore Longitudinal Study of Aging found no significant relationship between the trajectory of depressive symptoms and future carotid IMT.
CIMT progression rates have been associated with risk factors such as diabetes, smoking, hypercholesterolemia, and hypertension (Chambless et al. 2002; Ferrieres et al. 1999). CIMT has been used successfully to study arterial atherosclerotic disease in predicting cardiovascular disease outcomes (myocardial infarction, stroke), clinical coronary outcomes, determining the effectiveness of risk factor intervention, and in monitoring the progression of arterial wall thickness over time (Bots et al. 2003; Chambless et al. 1997; Grobbee and Bots 1994) In a meta-analysis of population-based CIMT studies, Lorenz et al. (2007) estimated the relative risk of myocardial infarction and stroke as 1.15 and 1.18, respectively (adjusted for age and gender), for each 0.10-mm thickness increase in common carotid IMT.
Methods
Study design and participants
Between June 2004 and October 2009, 464 police officers (active-duty and retired) among all officers in the Buffalo New York Police Department (estimated to be approximately 710 in 2004) were examined in the Buffalo Cardio-metabolic Occupational Police Stress (BCOPS) study. Women officers who were pregnant at the time of examination were excluded. Police officers perform a variety of duties. A typical routine day in this sample of officers may involve riding on patrol, walking a beat, answering complaint calls for police service, handling traffic accidents, investigating crimes, and writing reports. During routine patrol, officers may also be exposed to incidents considered to be traumatic, such as shootings, assaults, robberies, and homicides. Officers are required to work 10 h fixed shifts, including midnight shifts.
The data were collected at the Center for Health Research, School of Public Health and Health Professions, University at Buffalo, State University of New York. To be eligible for this current study, officers must have had no prior history of heart attack, stroke, bypass surgery, carotid artery endarterectomy, transient ischemic attack, or any physician-diagnosed coronary heart disease. The final sample included 412 officers with complete data (305 men and 107 women) who were currently employed, had complete information for CIMT, and had completed the Center for Epidemiologic Studies Depression (CES-D) Scale (Radloff 1977). Prior to any clinic examinations, the officers reviewed and signed informed consent forms. The Institutional Review Board at the University at Buffalo and the National Institute for Occupational Safety and Health (NIOSH) approved the study.
Measures
Assessment of carotid intima-media thickness
Certified sonographers used a standardized ultrasound protocol that was adopted from the Center for Medical Ultrasound at Wake Forest University. High-resolution B-mode carotid ultrasonography was performed using a 7.5- to 10-MHz transducer and a Biosound Esaote (AU5) ultrasound machine (Howard et al. 1993) Prior to the measurement of CIMT, the participants lay supine in a darkened, quiet room. A cool gel was applied to the area to be scanned and a preliminary exploratory transverse scan was performed to assess the participant’s anatomy and to determine the optimum angle for the CIMT scan. Standing at the head of the examination table, the sonographers scanned both the right and left extra-cranial carotid arteries. Starting at the optimal angle, standardized longitudinal images were acquired of the near and far walls of the distal 1.0 cm portion of the common carotid artery (CCA), the carotid bifurcation and proximal 1.0 cm at the optimum angle, and two additional scanning angles (30–45° anterior and 30–45° posterior). Mean common carotid artery (CCA) IMT (mm) is defined as the average of the CCA IMT measured at 12 sites in the right and left CCA. Mean maximum (MMXIMT) IMT (mm) is the average of the maximum IMT measured in the CCA, bifurcation, and internal carotid artery on both the right and left sides of the neck from three interrogation angles on the right and left side of the near and far walls (3 sites × 3 angles × 2 sides × 2 walls = 36) and was computed as the average IMT for all 36 image segments (Riley 2002). The scans were recorded on a ¾-inch (1.9 cm) high-resolution (Super VHS) video cassette and later digitized using ImagePro Plus software for measurement.
Established guidelines were used for ongoing quality control. The acceptable differences between any two ultrasound readers should not exceed <0.03 mm for the MMCCA and <0.05 mm for the MMXIMT. A phantom scan, using a tissue equivalent phantom, was performed every 2 weeks to ensure accurate calibration of the ultrasound machine and transducers.
Assessment of depressive symptoms
Depressive symptoms were measured using the Center for Epidemiological Studies Depression (CES-D) scale. The CES-D is a short scale that was designed to measure the symptoms of depression in the general population (Radloff 1977). Several dimensions of depression are measured including affective components of depression, psychomotor retardation, loss of appetite, and sleep disorder. The CES-D consists of 20 items with responses on a 4-point scale which represents the degree to which each symptom occurred during the past 7 days: 0 (rarely or none of the time, less than 1 day); 1 (some or little of the time, 1–2 days); 2 (occasionally or a moderate amount of time, 3–4 days); and 3 (most or all of the time, 5–7 days). These items are used to obtain an overall score (range = 0–60) of depressive symptoms. For analysis, the CES-D scores were categorized into quintiles: 1st quintile (0–<3), 2nd quintile (3–<5), 3rd quintile (5–<8), 4th quintile (8–<12), and 5th quintile (12–42) and also into two categories <16 (not depressed) and ≥16 (depressed).
Depressive symptoms are determined here by means of a valid and reliable questionnaire, but should not be construed at clinical depression. Clinical depression must either have a depressed mood or a loss of interest or pleasure in daily activities consistently for at least a 2-week period (American Psychiatric Association 2000 DSM-IV 1994). Our study was cross-sectional, and therefore, it was not possible to diagnose clinical depression in our sample.
Assessment of covariates
CVD risk components were based on cut-points established by the National Cholesterol Education Program Adult Treatment Panel III (NCEP ATP III), the American Heart Association and the National Heart, Lung, and Blood Institute, National Institutes of Health which included abdominal obesity (gender-specific waist circumference), impaired fasting blood glucose, elevated triglycerides, elevated blood pressure, and reduced gender-specific HDL cholesterol. Hypertension was defined as taking any medication for high blood pressure or having a systolic blood pressure of ≥140 mm Hg or a diastolic blood pressure of ≥90 mm Hg. The average of the second and third of three resting systolic and diastolic blood pressure readings was used. Diabetes was defined as taking any medication for diabetes or having a fasting serum glucose level of ≥126 mg/dL (Grundy et al. 2005). Participants were weighed, and height was measured without shoes. Body mass index (BMI) was calculated as weight (in kilograms) divided by height (in meters) squared. Waist circumference was measured at the midpoint between the lowest part of the costal margin in the mid-axillary line and highest point of the iliac crest. The average value of two measurements rounded to the nearest 0.5 cm was used in the analyses. If the two measurements had a difference of more than 0.5 cm, a third measurement was performed. Blood was collected from officers who had fasted for at least 12 h the previous night. Blood parameters were measured at Kaleida Laboratory, Buffalo, NY, by standard laboratory techniques on the Beckman Coulter LX20 clinical chemistry analyzer and included a blood lipid panel for HDL and triglycerides, and chemistry panels for glucose.
Officers were given self and interviewer-administered questionnaires to provide information on demographic characteristics, lifestyle behaviors, and medical history. For educational status, they checked one of eight choices from “less than 12 years of school” to “graduate degree;” these eight categories were later collapsed into three levels (<high school/GED, college <4 years, and college 4+ years). Officers were asked how often they consumed alcoholic beverages with one drink defined as a 12-oz. can or bottle of beer, one medium glass of wine (6 oz. or 170 gm), or one shot (1 oz. or 28.4 gm) of liquor. The total number of drinks per month (of each type) was summed and then divided by 4 to give the approximate total number of drinks consumed per week. Officers reported their smoking status as current, former, or never. Hours of sleep was assessed from questionnaire data. The average hours of sleep reported for the five previous weekdays were multiplied by five and the hours reported for the weekend days were multiplied by two. The hours were then summed and divided by seven to give the total hours of sleep per 24-h period during the previous 7 days.
Sleep quality was obtained from 19 self-rated individual questions that assessed various sleep quality-related factors over the previous 1-month period. These 19 items were grouped into seven components. Each component was scored by summing the scores of each item. Each item was weighted equally on a 0–3 scale. A global PSQI score was derived by summing up the seven component scores with a possible range of 0–21; a global score of >5 defined poor sleep quality (Buysse et al. 1989). The PSQI global score allows direct comparisons among groups, identifies groups that differ in the quality of sleep, and provides a single overall assessment of sleep quality. Studies have shown that the PSQI has high internal homogeneity, reliability, and validity (Buysse et al. 1989; Knutson et al. 2006).
Physical activity during the previous 7 days was obtained with the Seven-Day Physical Activity Recall questionnaire (Sallis et al. 1986). For three types of physical activity (occupational, household, and sports), participants reported the duration (hours per weekday, hours per weekend) and intensity (moderate, hard, very hard). A total physical activity score was then computed by summing the intensities of the three types of physical activity performed during the weekday and weekend, and multiplying that number by the reported duration.
Statistical analysis
Simple descriptive measures were calculated for all variables. Associations for all covariates with CES-D scores and CIMT were examined using the chi-square test of independence and analysis of variance (ANOVA). ANOVA and analysis of covariance (ANCOVA) were utilized to examine the mean values of CCA IMT and MMXIMT across quintiles of depressive symptoms. Depressive symptoms were categorized into quintiles in order to present mean values of the dependent variables which facilitate the interpretation of the results. The p values for linear trends were obtained from linear regression models utilizing the continuous forms of both dependent and independent variables. Effect modification was assessed for antidepressant medication use, BMI, smoking status, alcohol consumption status, physical activity status, history of hypertension and diabetes, race/ethnicity, gender, sleep duration, and sleep quality. Confounders were selected based on their associations with the main exposures and outcomes or on the scientific literature. The potential confounders were age, gender, race/ethnicity, educational level, cigarette smoking status, alcohol intake, waist circumference, HDL cholesterol, LDL cholesterol, triglycerides, glucose, diabetes, systolic blood pressure, hypertension, antidepressant medication use, and physical activity. All analyses were conducted in SAS version 9.2 2008 (SAS; Cary, NC).
Results
The mean age (±SD) of all officers (n = 412) was 41.0 ± 7.1 years (Table 1). The age ranges for men and women were 21–66 and 26–53 years, respectively. The majority of officers were Caucasian (76.8 %), 16.7 % were current smokers, and 19.9 % reported 8 drinks or more per week. Approximately 24 % of all officers had a history of hypertension and 2.7 % a history of diabetes. Women had slightly higher CES-D scores than men (8.7 ± 8.2 vs. 7.4 ± 6.6). In contrast, men had slightly higher mean CCA IMT (0.626 mm vs. 0.587 mm) and MMXIMT (0.801 mm vs. 0.729 mm) values than women.
Table 1.
Demographic and lifestyle characteristics by gender, BCOPS study
| Characteristics | Men (n = 305) |
Women (n = 107) |
Total (n = 412) |
|||
|---|---|---|---|---|---|---|
| N | Mean (SD) | N | Mean (SD) | N | Mean (SD) | |
| Age (years) | 305 | 41.1 (7.4) | 107 | 40.7 (6.1) | 412 | 41.0 (7.1) |
| BMI (kg/m2) | 303 | 30.3 (4.2) | 107 | 26.0 (4.7) | 410 | 29.2 (4.7) |
| Waist circumference (cm) | 305 | 99.1 (11.3) | 107 | 80.0 (11.6) | 412 | 94.2 (14.1) |
| Police service (years) | 302 | 14.9 (7.7) | 107 | 13.5 (6.8) | 409 | 14.6 (7.5) |
| Hours of sleep/day | 300 | 6.3 (1.2) | 106 | 6.4 (1.3) | 406 | 6.3 (1.2) |
| Sleep quality (global score) | 278 | 6.3 (3.2) | 104 | 7.0 (3.7) | 382 | 6.5 (3.3) |
| HDL cholesterol (mg/dL) | 304 | 42.2 (12.0) | 105 | 58.3 (15.8) | 409 | 46.3 (14.8) |
| LDL cholesterol (mg/dL) | 303 | 131.0 (33.5) | 104 | 118.9 (31.7) | 407 | 128.0 (33.4) |
| Triglycerides (mg/dL) | 304 | 153.5 (127.5) | 105 | 88.5 (130.6) | 409 | 136.8 (131.3) |
| Glucose (mg/dL) | 304 | 94.6 (13.9) | 106 | 86.3 (8.3) | 410 | 92.5 (13.2) |
| C-reactive protein (mg/L) | 304 | 3.23 (6.39) | 105 | 2.74 (3.26) | 409 | 3.10 (5.75) |
| Physical activity score | 303 | 21.0 (18.3) | 107 | 21.8 (17.6) | 410 | 21.3 (18.1) |
| Systolic blood pressure (mmHg) | 305 | 122.3 (11.3) | 107 | 116.5 (13.3) | 412 | 120.8 (12.1) |
| Depressive symptoms (CES-D score) | 305 | 7.4 (6.6) | 107 | 8.7 (8.2) | 412 | 7.8 (7.0) |
| CCA IMT (mm) | 305 | 0.626 (0.105) | 107 | 0.587 (0.078) | 412 | 0.616 (0.100) |
| MMXIMT (mm) | 305 | 0.801 (0.150) | 107 | 0.729 (0.102) | 412 | 0.782 (0.143) |
| Ethnicity | % | % | % | |||
| European American | 237 | 78.2 | 78 | 72.9 | 315 | 76.8 |
| African American | 53 | 17.5 | 29 | 27.1 | 82 | 20.0 |
| Hispanic American | 13 | 4.3 | 0 | 0 | 13 | 3.2 |
| Education | ||||||
| <=High school/GED | 38 | 12.6 | 4 | 3.7 | 42 | 10.2 |
| College <4 years | 160 | 53.0 | 66 | 61.7 | 226 | 55.3 |
| College 4+ years | 104 | 34.4 | 37 | 34.6 | 141 | 34.5 |
| Marital status | ||||||
| Single | 28 | 9.3 | 23 | 21.5 | 51 | 12.5 |
| Married/unmarried couple | 236 | 78.4 | 63 | 58.9 | 299 | 73.3 |
| Divorced/separated | 37 | 12.3 | 21 | 19.6 | 58 | 14.2 |
| Cigarette smoking status | ||||||
| Never | 199 | 65.7 | 46 | 43.8 | 245 | 60.0 |
| Former | 64 | 21.1 | 31 | 29.5 | 95 | 23.3 |
| Current | 40 | 13.2 | 28 | 26.7 | 68 | 16.7 |
| Alcohol intake (drinks/week) | ||||||
| None | 51 | 16.7 | 26 | 24.3 | 77 | 18.7 |
| <1 | 46 | 15.1 | 23 | 21.5 | 69 | 16.7 |
| 1–3 | 71 | 23.3 | 22 | 20.6 | 93 | 22.6 |
| 4–7 | 69 | 22.6 | 22 | 20.6 | 91 | 22.1 |
| 8+ | 68 | 22.3 | 14 | 13.1 | 82 | 19.9 |
| Sleep quality | ||||||
| Good | 130 | 42.6 | 46 | 43.0 | 176 | 42.7 |
| Poor | 148 | 48.5 | 58 | 54.2 | 206 | 50.0 |
| Antidepressant medication use | 19 | 6.3 | 12 | 11.2 | 31 | 7.6 |
| Hypertension | 80 | 26.2 | 18 | 16.8 | 98 | 23.8 |
| Diabetes | 10 | 3.3 | 1 | 0.9 | 11 | 2.7 |
Hypertension was defined as taking any medication for high blood pressure or SBP ≥ 140 or DBP ≥ 90
Diabetes was defined as taking any medication for diabetes or fasting serum glucose ≥126
BMI body mass index, BP blood pressure, CIMT carotid intima-media thickness, CES-D center for epidemiologic studies depression scale
Results for the association between demographic, lifestyle characteristics, and CES-D scores are presented in Table 2. Low-density lipoprotein (LDL) cholesterol and triglycerides generally increased with increasing quintiles of CES-D scores but the associations were not statistically significant. Race/ethnicity was associated with CES-D scores, P = 0.029. Use of antidepressant medications was also associated with CES-D scores, P = 0.004. Table 3 provides associations between selected demographics, traditional CVD risk factors, CCA IMT, and MMXIMT. Most results were in the expected direction. LDL cholesterol, glucose levels, diabetes, and hypertension were positively and significantly correlated with both CIMT measures, whereas high-density lipoprotein (HDL) was inversely and significantly associated with both. Mean levels of CCA IMT and MMXIMT differed significantly by race/ethnicity, with Caucasians having the lowest mean levels and Hispanic-American officers having the highest mean levels of both CCA IMT (P = 0.007) and MMXIMT (P = 0.007).
Table 2.
Selected characteristics by quintiles of CES-D score, BCOPS study
| Quintiles of CES-D score |
P | |||||
|---|---|---|---|---|---|---|
| 0–2.9 (n = 88) | 3–4.9 (n = 74) | 5–7.9 (n = 80) | 8–11.9 (n = 80) | 12–42 (n = 90) | ||
| Age (years) | 40.5 ± 8.1 | 40.8 ± 6.3 | 41.4 ± 7.5 | 41.3 ± 6.6 | 40.8 ± 7.0 | 0.833 |
| BMI (kg/m2) | 28.8 ± 3.4 | 29.8 ± 4.9 | 28.7 ± 4.8 | 29.8 ± 5.6 | 28.8 ± 4.6 | 0.487 |
| Waist circumference (cm) | 93.3 ± 12.2 | 94.6 ± 14.4 | 92.8 ± 14.0 | 96.6 ± 15.9 | 93.7 ± 14.2 | 0.827 |
| Police service (years) | 14.0 ± 8.0 | 14.2 ± 6.4 | 15.9 ± 8.1 | 14.3 ± 7.7 | 14.4 ± 6.9 | 0.999 |
| Hours of sleep per 24-h period | 6.4 ± 1.3 | 6.1 ± 1.2 | 6.4 ± 1.2 | 6.4 ± 1.2 | 6.3 ± 1.2 | 0.726 |
| Sleep quality | 5.0 ± 2.8 | 5.4 ± 2.6 | 5.5 ± 3.4 | 7.4 ± 3.0 | 8.9 ± 3.0 | <0.0001 |
| HDL cholesterol (mg/dL) | 47.0 ± 14.8 | 43.3 ± 13.8 | 46.7 ± 13.9 | 47.8 ± 16.2 | 46.6 ± 15.1 | 0.702 |
| LDL cholesterol (mg/dL) | 125.8 ± 31.1 | 126.4 ± 30.9 | 124.0 ± 28.9 | 127.1 ± 35.5 | 135.5 ± 38.7 | 0.160 |
| Triglycerides (mg/dL) | 126.2 ± 106.6 | 140.5 ± 151.7 | 112.9 ± 80.3 | 136.6 ± 103.5 | 165.7 ± 181.1 | 0.087 |
| Glucose (mg/dL) | 92.1 ± 10.9 | 92.5 ± 9.6 | 92.4 ± 12.6 | 91.5 ± 10.3 | 93.7 ± 19.5 | 0.753 |
| C-reactive protein (mg/L) | 2.8 ± 3.3 | 2.2 ± 1.9 | 3.7 ± 8.8 | 4.2 ± 8.1 | 2.6 ± 3.0 | 0.959 |
| Physical activity score | 20.7 ± 17.2 | 21.6 ± 15.8 | 19.8 ± 16.6 | 21.1 ± 17.0 | 22.9 ± 22.6 | 0.784 |
| Systolic blood pressure (mmHg) | 120.2 ± 12.0 | 121.6 ± 11.0 | 121.0 ± 13.7 | 121.0 ± 11.3 | 120.4 ± 12.5 | 0.721 |
| Race/ethnicity (%) | ||||||
| Caucasian | 83.0 | 63.0 | 77.5 | 74.7 | 83.3 | 0.029 |
| African American | 17.0 | 31.5 | 21.3 | 20.3 | 12.2 | |
| Hispanic American | 0 | 5.5 | 1.3 | 5.0 | 4.4 | |
| Education (%) | ||||||
| ≤High school/GED | 10.2 | 12.3 | 8.8 | 8.9 | 11.2 | 0.937 |
| College <4 years | 60.2 | 52.1 | 51.3 | 55.7 | 56.2 | |
| College ≥4 years | 29.6 | 35.6 | 40.0 | 35.4 | 32.6 | |
| Marital status (%) | ||||||
| Single | 10.2 | 15.3 | 8.8 | 13.9 | 14.6 | 0.909 |
| Married/unmarried | 76.1 | 72.2 | 77.5 | 72.2 | ||
| Divorced/separated | 13.6 | 12.5 | 13.8 | 13.9 | 16.9 | |
| Smoking status (%) | ||||||
| Never | 58.6 | 61.6 | 65.0 | 54.4 | 60.0 | 0.768 |
| Former | 26.4 | 24.7 | 21.3 | 24.1 | 20.0 | |
| Current | 15.0 | 13.7 | 12.5 | 21.5 | 20.0 | |
| Alcohol intake (drinks/wk) | ||||||
| None | 20.5 | 24.3 | 17.5 | 15.0 | 16.7 | |
| <1 | 13.6 | 24.3 | 20.0 | 11.3 | 15.6 | |
| 1–3 | 30.7 | 14.9 | 28.8 | 18.8 | 18.9 | |
| 4–7 | 21.6 | 18.9 | 15.0 | 28.8 | 25.6 | |
| ≥8 | 13.6 | 17.6 | 18.8 | 26.3 | 23.3 | 0.126 |
| Sleep quality | ||||||
| Good | 63.9 | 58.8 | 60.3 | 32.9 | 17.7 | <0.0001 |
| Poor | 36.1 | 41.2 | 39.7 | 67.1 | 82.3 | |
| Antidepressant medication | 5.7 | 5.5 | 5.0 | 2.5 | 17.8 | 0.004 |
| Hypertension (%) | 25.0 | 24.3 | 26.3 | 21.3 | 22.2 | 0.944 |
| Diabetes (%) | 2.3 | 4.1 | 5.0 | 0 | 2.2 | 0.306 |
Results are means ± standard deviations or percentages
The p values for continuous variables are from linear regression models, and for the categorical variables, chi-square
BMI body mass index, BP blood pressure, HDL high-density lipoprotein, LDL low-density lipoprotein
Table 3.
Selected characteristics by CCA IMT and MMXIMT measures, BCOPS study
| Covariates | CCA IMT | MMXIMT |
|---|---|---|
| Age (years) | 0.5093, <0.0001 | 0.5425, <0.0001 |
| BMI (kg/m2) | 0.2509, <0.0001 | 0.2696, <0.0001 |
| Waist circumference (cm) | 0.2634, <0.0001 | 0.2846, <0.0001 |
| Police service (years) | 0.3935, <0.0001 | 0.4349, <0.0001 |
| Hours of sleep per 24-h period | −0.0066, 0.895 | −0.0282, 0.571 |
| Sleep quality | −0.0444, 0.387 | −0.0856, 0.095 |
| HDL cholesterol (mg/dL) | −0.1469, 0.0029 | −0.1516, 0.0021 |
| LDL cholesterol (mg/dL) | 0.1327, 0.0074 | 0.1360, 0.0060 |
| Triglycerides (mg/dL) | 0.0987, 0.0460 | 0.0633, 0.2014 |
| Glucose (mg/dL) | 0.1661, 0.0007 | 0.2012, <0.0001 |
| C-reactive protein (mg/L) | 0.0839, 0.0901 | 0.0598, 0.2277 |
| Physical activity score | 0.0756, 0.126 | 0.0751, 0.129 |
| Systolic blood pressure (mmHg) | 0.2295, <0.0001 | 0.2155, <0.0001 |
| Race/ethnicity | ||
| European American | 0.608 ± 0.100 | 0.773 ± 0.139 |
| African American | 0.640 ± 0.095 | 0.801 ± 0.115 |
| Hispanic American | 0.665 ± 0.106 | 0.889 ± 0.285 |
| p value* | 0.007 | 0.007 |
| Education | ||
| <=High school/GED | 0.627 ± 0.090 | 0.813 ± 0.137 |
| College <4 years | 0.621 ± 0.110 | 0.780 ± 0.155 |
| College 4+ years | 0.604 ± 0.086 | 0.777 ± 0.123 |
| p value† | 0.202 | 0.153 |
| Marital status | ||
| Single | 0.595 ± 0.097 | 0.742 ± 0.116 |
| Married/unmarried couple | 0.613 ± 0.095 | 0.785 ± 0.151 |
| Divorced/separated | 0.646 ± 0.124 | 0.802 ± 0.116 |
| p value* | 0.020 | 0.071 |
| Cigarette smoking status | ||
| Never | 0.607 ± 0.093 | 0.772 ± 0.114 |
| Former | 0.638 ± 0.117 | 0.813 ± 0.188 |
| Current | 0.619 ± 0.100 | 0.773 ± 0.160 |
| p value* | 0.037 | 0.055 |
| Alcohol intake (drinks/week) | ||
| None | 0.543 ± 0.078 | 0.676 ± 0.154 |
| <1 | 0.603 ± 0.082 | 0.777 ± 0.136 |
| 1–3 | 0.630 ± 0.105 | 0.789 ± 0.139 |
| 4–7 | 0.608 ± 0.089 | 0.770 ± 0.129 |
| 8+ | 0.619 ± 0.120 | 0.791 ± 0.175 |
| p value†† | 0.441 | 0.283 |
| Sleep quality | ||
| Good | 0.626 ± 0.008 | 0.803 ± 0.011 |
| Poor | 0.607 ± 0.007 | 0.763 ± 0.010 |
| p value* | 0.069 | 0.008 |
| Antidepressant medication use | ||
| Yes | 0.616 ± 0.105 | 0.890 ± 0.169 |
| No | 0.616 ± 0.100 | 0.890 ± 0.217 |
| p value* | 0.977 | 0.986 |
| Hypertension | ||
| Yes | 0.663 ± 0.123 | 0.843 ± 0.192 |
| No | 0.602 ± 0.088 | 0.764 ± 0.119 |
| p value* | <0.0001 | <0.0001 |
| Diabetes | ||
| Yes | 0.687 ± 0.100 | 0.979 ± 0.364 |
| No | 0.614 ± 0.100 | 0.777 ± 0.128 |
| p value* | 0.016 | <0.0001 |
Results are Pearson’s correlation coefficients and mean ± SD
p value for any difference between the means
p value from polynomial orthogonal contrast linear trend
p value from linear regression models
After adjustment for age, gender, race, education level, cigarette smoking status, alcohol intake, body mass index (BMI), HDL cholesterol, LDL cholesterol, triglycerides, glucose, and hypertension, officers with CES-D scores >16 had a higher mean CCA IMT value (0.628 ± 0.013) than officers with lower CES-D scores, but the difference was not statistically significant (P = 0.130) (data not shown). Similar results were observed with MMXIMT. The results in Table 4 show no significant association for CES-D scores with CCA IMT or MMXIMT, before or after adjustment for covariates.
Table 4.
Unadjusted and adjusted mean values of the CCA IMT and MMXIMT across quintiles of CES-D score, BCOPS study
| Quintiles of CES-D score |
p value* | |||||
|---|---|---|---|---|---|---|
| 0–2.9 (n = 88) | 3–4.9 (n = 74) | 5–7.9 (n = 80) | 8–11.9 (n = 80) | 12–42 (n = 90) | ||
| CCA IMT (mm) | ||||||
| Model 1 | 0.617 ± 0.114 | 0.607 ± 0.089 | 0.612 ± 0.101 | 0.616 ± 0.093 | 0.624 ± 0.102 | 0.479 |
| Model 2 | 0.621 ± 0.013 | 0.600 ± 0.013 | 0.612 ± 0.013 | 0.612 ± 0.013 | 0.630 ± 0.013 | 0.300 |
| Model 3 | 0.652 ± 0.021 | 0.629 ± 0.020 | 0.646 ± 0.021 | 0.640 ± 0.021 | 0.660 ± 0.020 | 0.356 |
| MMXIMT (mm) | ||||||
| Model 1 | 0.785 ± 0.147 | 0.784 ± 0.172 | 0.784 ± 0.142 | 0.777 ± 0.120 | 0.781 ± 0.133 | 0.735 |
| Model 2 | 0.805 ± 0.018 | 0.788 ± 0.018 | 0.795 ± 0.019 | 0.779 ± 0.018 | 0.800 ± 0.017 | 0.663 |
| Model 3 | 0.887 ± 0.028 | 0.867 ± 0.028 | 0.878 ± 0.028 | 0.861 ± 0.029 | 0.884 ± 0.028 | 0.763 |
Values are means (standard deviations) for unadjusted models or means (standard errors) for adjusted models
Model 1: Unadjusted
Model 2: Adjusted for age, gender, race, educational level, cigarette smoking status, and alcohol intake
Model 3: Adjusted for age, gender, race, educational level, cigarette smoking status, alcohol intake, waist circumference, HDL cholesterol, LDL cholesterol, triglycerides, glucose, diabetes, systolic blood pressure, hypertension, antidepressant medication use, and physical activity
CCA IMT common carotid intima-media thickness, MMXIMT maximum carotid intima-media thickness, CES-D center for epidemiologic studies depression scale
p values are from linear orthogonal contrasts
To help clarify associations between depressive symptoms, CVD risk factors, and CIMT, we stratified by traditional CVD risk factors based on the cut-points recommended by the National Cholesterol Education Program Adult Treatment Panel III (NCEP ATP III), the American Heart Association and the National Heart, Lung, and Blood Institute, National Institutes of Health. With the exception of hypertension (SPB ≥ 140 mm Hg; DBP ≥ 90 mm Hg or medication use), no significant associations were observed between depressive symptoms and CIMT after stratification.
Hypertension status significantly modified the association between CES-D and CCA IMT (interaction P = 0.088) and between CES-D and MMXIMT (interaction P = 0.083). Table 5 displays mean values of CCA IMT and MMXIMT across quintiles of CES-D score, stratified by hypertension status. Among officers without hypertension, depressive symptoms were positively and significantly associated with CCA IMT in the unadjusted model (P = 0.041). This association remained statistically significant after inclusion of several confounders and CVD risk factors (P = 0.030). The associations between CES-D and MMXIMT were not statistically significant among the officers with or without hypertension.
Table 5.
Unadjusted and adjusted mean values of the CCA IMT and MMXIMT across quintiles of CES-D score, stratified by hypertension, BCOPS study
| Quintiles of CES-D score |
p value* | |||||
|---|---|---|---|---|---|---|
| 0–2.9 (n = 88) | 3–4.9 (n = 74) | 5–7.9 (n = 80) | 8–11.9 (n = 80) | 12–42 (n = 90) | ||
| CCA IMT (mm) | ||||||
| Hypertension | n = 19 | n = 18 | n = 20 | n = 17 | n = 19 | |
| Model 1 | 0.694 ± 0.178 | 0.658 ± 0.115 | 0.667 ± 0.139 | 0.673 ± 0.083 | 0.622 ± 0.065 | 0.157 |
| Model 2 | 0.715 ± 0.034 | 0.659 ± 0.034 | 0.663 ± 0.037 | 0.674 ± 0.038 | 0.642 ± 0.037 | 0.144 |
| Model 3 | 0.781 ± 0.051 | 0.710 ± 0.049 | 0.747 ± 0.052 | 0.720 ± 0.055 | 0.701 ± 0.050 | 0.116 |
| No hypertension | n = 69 | n = 56 | n = 60 | n = 63 | n = 71 | |
| Model 1 | 0.596 ± 0.078 | 0.591 ± 0.074 | 0.593 ± 0.077 | 0.601 ± 0.090 | 0.625 ± 0.110 | 0.041 |
| Model 2 | 0.590 ± 0.014 | 0.583 ± 0.014 | 0.593 ± 0.014 | 0.593 ± 0.013 | 0.622 ± 0.013 | 0.013 |
| Model 3 | 0.610 ± 0.023 | 0.600 ± 0.024 | 0.610 ± 0.024 | 0.611 ± 0.024 | 0.637 ± 0.023 | 0.030 |
| MMXIMT (mm) | ||||||
| Hypertension | ||||||
| Model 1 | 0.866 ± 0.221 | 0.877 ± 0.261 | 0.849 ± 0.207 | 0.864 ± 0.107 | 0.764 ± 0.108 | 0.126 |
| Model 2 | 0.919 ± 0.054 | 0.861 ± 0.053 | 0.848 ± 0.058 | 0.867 ± 0.059 | 0.786 ± 0.057 | 0.063 |
| Model 3 | 1.192 ± 0.071 | 1.084 ± 0.067 | 1.114 ± 0.072 | 1.140 ± 0.075 | 1.049 ± 0.068 | 0.078 |
| No hypertension | ||||||
| Model 1 | 0.763 ± 0.111 | 0.754 ± 0.120 | 0.762 ± 0.106 | 0.753 ± 0.113 | 0.785 ± 0.139 | 0.346 |
| Model 2 | 0.760 ± 0.018 | 0.752 ± 0.019 | 0.764 ± 0.018 | 0.745 ± 0.017 | 0.784 ± 0.017 | 0.288 |
| Model 3 | 0.752 ± 0.030 | 0.740 ± 0.030 | 0.750 ± 0.030 | 0.731 ± 0.030 | 0.768 ± 0.029 | 0.530 |
Interaction p value = 0.062
Values are means (standard deviations) for unadjusted models or means (standard errors) for adjusted models
Model 1: Unadjusted
Model 2: Adjusted for age, gender, race, educational level, cigarette smoking status, and alcohol intake
Model 3: Adjusted for age, gender, race, educational level, cigarette smoking status, alcohol intake, waist circumference, HDL cholesterol, LDL cholesterol, triglycerides, glucose, diabetes, systolic blood pressure, hypertension, antidepressant medication use, and physical activity
Interaction by hypertension status for CCA IMT: p = 0.088
Interaction by hypertension status for MMXIMT: p = 0.083
CIMT carotid intima-media thickness, CES-D center for epidemiologic studies depression scale
p values are from linear orthogonal contrasts
Although sleep quality did not significantly modify the association between CES-D and CIMT, the associations among officers who reported poor sleep quality versus those who reported good sleep quality were substantially different (though not statistically significant) to warrant mention in this paper. Among officers who reported poor sleep quality, mean values of both CCA IMT and MMXIMT increased as depressive symptoms (CES-D scores) increased; adjusted p values for linear trends were =0.071 and 0.083, respectively. Among officers who reported good sleep quality, the associations of depressive symptoms with CCA IMT and MMXIMT did not show a similar positive relationship nor were they statistically significant.
Discussion
The goal of this study was to investigate the cross-sectional association of depressive symptoms with subclinical cardiovascular markers CIMT and MMXIMT among police officers. As expected, traditional risk factors remained strong predictors of CIMT. Age, BMI, LDL cholesterol, and glucose levels were positively and significantly correlated with CIMT measures, whereas high-density lipoprotein (HDL) was inversely and significantly associated with both. We stratified by traditional CVD risk factors to reveal whether any of these risk factors might modify the association between depressive symptoms and CIMT. No significant differences were noted in the associations between depressive symptoms and CIMT after stratification with one exception: hypertension. A significant positive association between depressive symptoms and CIMT was observed in officers who were free of hypertension. Additionally, hypertension significantly modified the association between CES-D and CCAIMT. This result indicated that depressive symptoms may be independently associated with CIMT, yet only among participants free of hypertension. Recent work on depression and hypertension has provided evidence of increased sympathetic activity and increased blood pressure reactivity (Jonas and Lando 2000; Jonas et al. 1997; Bowman and Nicklin 1997; Veith et al. 1994; Waked and Jutai 1990). These studies suggest that depression may have an effect on the cardiovascular system that could lead to the development of hypertension and possible future CVD. Our results also showed that among officers who reported poor sleep quality (Table 6), mean levels of CIMT tended to increase as depressive symptoms increased. Even though sleep quality did not significantly modify the main association, our results suggest that poor sleep quality may act synergistically with depressive symptoms to increase CIMT. Violanti et al. (2009) found that police officers working midnight shifts combined with either shorter sleep duration or increased overtime may be at an increased risk for metabolic syndrome. The prevalence of metabolic syndrome among officers working the midnight shift was higher than that found in the National Health and Nutrition Examination Survey (NHANES III) 1988–1994 (Ford et al. 2002). Karlsson et al. (2001) found that obesity, high triglycerides, and low concentrations of HDL cholesterol seem to cluster together more often in shift workers than in day workers. Lasfargues et al. (1996) found night-shift workers have significantly higher levels of triglycerides, smoking, and obesity than controls. In a review of the literature, Wolk and Somers (2007) found that the weight of evidence suggested that sleep deprivation and shift work independently lead to the development of both insulin resistance and individual components of the metabolic syndrome. Other studies found the metabolic effects of shift work to include abdominal obesity, lower HDL cholesterol and higher triglycerides, and changes in glucose intolerance (Nagaya et al. 2002). Mean levels of CCA IMT and MMXIMT differed significantly by race/ethnicity, with Caucasians having the lowest mean levels and Hispanic-American officers having the highest mean levels of both CCA IMT (P = 0.007) and MMXIMT (P = 0.007). The small number of Hispanic Americans in our study prevented any meaningful conclusions concerning CIMT and depressive symptoms. African Americans had significantly greater mean CIMT than did Caucasians in our cohort; however, no significant interactions with depressive symptoms were found. This was not surprising, as African Americans are more likely to have a higher prevalence of CVD than whites and are also 1.5 times as likely as whites to have hypertension and 10 % less likely than whites to have their blood pressure under control (http://www.cdc.gov/nchs/data/series/sr_10/sr10_249.pdf).
Table 6.
Unadjusted and adjusted mean values of the CCA IMT and MMXIMT across quintiles of CES-D score, stratified by sleep quality, BCOPS study
| Quintiles of CES-D score |
p value* | |||||
|---|---|---|---|---|---|---|
| 0–2.9 (n = 83) | 3–4.9 (n = 68) | 5–7.9 (n = 73) | 8–11.9 (n = 73) | 12–42 (n = 85) | ||
| CCA IMT (mm) | ||||||
| Poor sleep quality | (n = 30) | (n = 28) | (n = 29) | (n = 49) | (n = 70) | |
| Model 1 | 0.587 ± 0.083 | 0.597 ± 0.072 | 0.595 ± 0.093 | 0.614 ± 0.091 | 0.618 ± 0.085 | 0.060 |
| Model 2 | 0.600 ± 0.018 | 0.596 ± 0.018 | 0.603 ± 0.018 | 0.607 ± 0.015 | 0.626 ± 0.014 | 0.093 |
| Model 3 | 0.615 ± 0.030 | 0.608 ± 0.028 | 0.618 ± 0.028 | 0.619 ± 0.028 | 0.644 ± 0.027 | 0.071 |
| Good sleep quality | (n = 53) | (n = 40) | (n = 44) | (n = 24) | (n = 15) | |
| Model 1 | 0.636 ± 0.129 | 0.618 ± 0.102 | 0.611 ± 0.097 | 0.617 ± 0.107 | 0.664 ± 0.165 | 0.467 |
| Model 2 | 0.634 ± 0.021 | 0.602 ± 0.020 | 0.609 ± 0.021 | 0.624 ± 0.025 | 0.667 ± 0.029 | 0.159 |
| Model 3 | 0.697 ± 0.039 | 0.661 ± 0.038 | 0.677 ± 0.039 | 0.672 ± 0.043 | 0.722 ± 0.044 | 0.331 |
| MMXIMT (mm) | ||||||
| Poor sleep quality | ||||||
| Model 1 | 0.736 ± 0.094 | 0.755 ± 0.103 | 0.750 ± 0.112 | 0.777 ± 0.126 | 0.775 ± 0.125 | 0.091 |
| Model 2 | 0.751 ± 0.024 | 0.745 ± 0.023 | 0.757 ± 0.023 | 0.762 ± 0.019 | 0.782 ± 0.018 | 0.104 |
| Model 3 | 0.730 ± 0.039 | 0.721 ± 0.036 | 0.734 ± 0.037 | 0.738 ± 0.037 | 0.765 ± 0.036 | 0.083 |
| Good sleep quality | ||||||
| Model 1 | 0.815 ± 0.168 | 0.808 ± 0.212 | 0.794 ± 0.159 | 0.769 ± 0.119 | 0.826 ± 0.176 | 0.890 |
| Model 2 | 0.839 ± 0.031 | 0.804 ± 0.029 | 0.814 ± 0.031 | 0.799 ± 0.036 | 0.844 ± 0.042 | 0.956 |
| Model 3 | 1.095 ± 0.051 | 1.052 ± 0.049 | 1.075 ± 0.051 | 1.038 ± 0.056 | 1.074 ± 0.056 | 0.494 |
Values are means (standard deviations) for unadjusted models or means (standard errors) for adjusted models
Model 1: Unadjusted
Model 2: Adjusted for age, gender, race, educational level, cigarette smoking status, and alcohol intake
Model 3: Adjusted for age, gender, race, educational level, cigarette smoking status, alcohol intake, waist circumference, HDL cholesterol, LDL cholesterol, triglycerides, glucose, diabetes, systolic blood pressure, hypertension, antidepressant medication use, and physical activity
Interaction by sleep quality for CCA IMT: p = 0.703
Interaction by sleep quality for MMXIMT: p = 0.249
CCA IMT common carotid intima-media thickness, MMXIMT maximum carotid intima-media thickness, CES-D center for epidemiologic studies depression scale
p values are from linear orthogonal contrasts
In a recent study, higher levels of hopelessness (a diagnostic criterion of depression) were associated with increased CIMT (Whipple et al. 2011). The authors stated that hopelessness confers an independent risk of CVD. For minority officers, there may be social conditions or exposures within police work that increase the risk of both depressive symptoms and hopelessness.
Behaviors related to stress or depression may also increase the risk for CVD in officers. The low physical fitness level found among police officers may be an indicator. Williams (1987) found that a substantial number of officers in their sample were at elevated risk for atherosclerotic heart disease: 76 % had elevated cholesterol, 26 % had elevated triglycerides, and 60 % elevated body fat composition. Price et al. (1978) concluded that middle-aged police officers had CVD risk above that of the general population. Joseph et al. (2009) found that police officers have increased levels of atherosclerosis compared with a general population sample, which was not fully explained by elevated CVD risk factors, thereby potentially implicating other mechanisms whereby law enforcement work may increase CVD risk. Franke and Anderson (1994) found that public safety officers had a higher probability of developing CHD than did the Framingham Heart Study population. Steinhardt et al. (1991) found an inverse association between cardiovascular fitness and medical claims among police officers. Of interest is the fact that police officers either suffer from disease or die at a much earlier age than do reference groups such as municipal workers or the general US population (Violanti et al. 1998; Franke et al. 1998). Officers also died from CVD at earlier ages than the general population (Violanti et al. 1998). This suggests the possible influence of lifestyle risk factors for those diseases, including psychological stress and depression.
This study is cross-sectional and cannot determine the causal direction between depressive symptoms and CIMT. Future prospective investigations may help to clarify this issue. Other limitations of this study are the lack of complete recruitment of all members of the police force, residual confounding, and the possibility of selection bias. To clarify whether officers who were examined were representative of all officers, we compared those officers who participated versus those who did not; summary characteristics were as follows: 26 versus 23 % women; 30 versus 28 % above 45 years of age; 66 versus 71 % police officers (vs. higher rank); and 45 versus 39 % hired after 1990, respectively. The results suggest that findings are likely to be generalizable to the entire Buffalo Police Department. The potential for residual confounding in this analysis could remain due to incomplete adjustment, and there could be other unmeasured variables that could not be adjusted for in the analysis. Another limitation of the study is the limited period of time for which information on depressive symptoms is available (i.e., 7 days). Data on the history of depressive symptoms or depressive disorders were not available for this cohort. If the association was causal, it might take years of exposure to depressive symptoms before an adverse effect on carotid IMT would be evident.
This study has the advantage of being conducted in a controlled clinical setting, where the assessment of many CVD risk factors (such as blood pressure or cholesterol) is conducted by trained clinic personnel. Data collection for all studies was performed at the same site, using a standardized protocol during similar time frames by the same research team. As suggested by Joseph et al. (2009), subclinical CIMT is a predictive measure of future CVD disease. The use of subclinical markers prior to CVD event manifestation is beneficial, in that preventive efforts may be initiated well in advance of clinically apparent disease.
In sum, the present study suggests that, other than when stratified by hypertension, no significant associations were observed for depressive symptoms with CCA IMT and MMXIMT, after adjustment for demographics and traditional CVD risk factors. However, among officers without hypertension, mean levels of CCA IMT increased with increasing quintiles of CES-D scores. This association was statistically significant after adjustment for several confounders and CVD risk factors (BMI, HDL cholesterol, LDL cholesterol, triglycerides, and serum glucose levels). This result may reflect difficulty detecting an association of depressive symptoms with CIMT in individuals with hypertension due to the strong influence of hypertension on CIMT, whereas such an association may be easier to detect in those free of hypertension. If confirmed in other studies and in a prospective design, efforts to reduce depressive symptoms and to prevent its occurrence might prevent increased CIMT. There are some studies which do provide directional evidence that depressive symptoms may have an adverse effect on the cardiovascular system that could lead to the development of hypertension and CVD (Waked and Jutai 1990; Julius 1988). Future prospective work is planned with the present police cohort to help clarify such possible directional relationships between depressive symptoms and CVD. It will also be necessary to examine not only depressive symptoms, but other variables associated with police work such as hopelessness and behavioral lifestyles that may further exacerbate earlier signs of cardiovascular disease.
Acknowledgments
This work was supported by the National Institute for Occupational Safety and Health (NIOSH), contract no. 200–2003–01580. The findings and conclusions in this article are those of the authors and do not necessarily represent the views of the National Institute for Occupational Safety and Health.
Footnotes
Conflict of interest The authors declare that they have no conflict of interest.
Contributor Information
John M. Violanti, Email: violanti@buffalo.edu, Department of Social and Preventive Medicine, School of Public Health and Health Professions, University at Buffalo, State University of New York, 270 Farber Hall, Buffalo, NY 14214, USA.
Luenda E. Charles, Biostatistics and Epidemiology Branch, Health Effects Laboratory Division, National Institute for Occupational Safety and Health, Centers for Disease Control and Prevention, Morgantown, WV, USA
Ja K. Gu, Biostatistics and Epidemiology Branch, Health Effects Laboratory Division, National Institute for Occupational Safety and Health, Centers for Disease Control and Prevention, Morgantown, WV, USA
Cecil M. Burchfiel, Biostatistics and Epidemiology Branch, Health Effects Laboratory Division, National Institute for Occupational Safety and Health, Centers for Disease Control and Prevention, Morgantown, WV, USA
Michael E. Andrew, Biostatistics and Epidemiology Branch, Health Effects Laboratory Division, National Institute for Occupational Safety and Health, Centers for Disease Control and Prevention, Morgantown, WV, USA
P. Nedra Joseph, The University of Chicago Comprehensive Cancer Center, Epidemiology and Research Recruitment Core, Chicago, IL, USA.
Joan M. Dorn, Department of Exercise and Nutrition Sciences, School of Public Health and Health Professions, State University of New York at Buffalo, Buffalo, NY, USA
References
- American Psychiatric Association. Diagnostic and statistical manual of mental disorders. 4th edn. Washington, DC: American Psychiatric Association; 2000. [Google Scholar]
- Appels A, Mulder P. Excess fatigue as a precursor of myocardial infarction. Eur Heart J. 1988;9:758–764. doi: 10.1093/eurheartj/9.7.758. [DOI] [PubMed] [Google Scholar]
- Barefoot JC, Schroll M. Symptoms of depression, acute myocardial infarction, and total mortality in a community sample. Circulation. 1996;93:1976–1980. doi: 10.1161/01.cir.93.11.1976. [DOI] [PubMed] [Google Scholar]
- Berg AM, Hem E, Lau B, Haseth K, Ekeberg O. Stress in the Norwegian police service. Occup Med. 2005;55:113–120. doi: 10.1093/occmed/kqi023. [DOI] [PubMed] [Google Scholar]
- Bots ML, Evans GW, Riley WA, Grobbee DE. Carotid intima-media thickness measurements in intervention studies: design options, progression rates, and sample size considerations: a point of view. Stroke. 2003;34:2985–2994. doi: 10.1161/01.STR.0000102044.27905.B5. [DOI] [PubMed] [Google Scholar]
- Bowman MA, Nicklin DE. Family medicine new guide to clinical preventive services published by the US Preventive Services Task Force. Depression and other stressors associated with hypertension. JAMA. 1997;277:1857–1858. [Google Scholar]
- Buysse DJ, Reynolds CF, III, Monk TH, Berman SR, Kupfer DJ. The Pittsburgh sleep quality index: a new instrument for psychiatric practice and research. Psych Res. 1989;28:193–213. doi: 10.1016/0165-1781(89)90047-4. [DOI] [PubMed] [Google Scholar]
- Chambless LE, Heiss G, Folsom AR, Rosamond W, Szklo M, Sharrett AR, Clegg LX. Association of coronary heart disease incidence with carotid arterial wall thickness and major risk factors: the atherosclerosis risk in communities (ARIC) study, 1987–1993. Am J Epidemiol. 1997;146:483–494. doi: 10.1093/oxfordjournals.aje.a009302. [DOI] [PubMed] [Google Scholar]
- Chambless LE, Folsom AR, Davis V, Sharrett R, Heiss G, Sorlie P, Szklo M, Howard G, Evans GW. Risk factors for progression of common carotid atherosclerosis: the atherosclerosis risk in communities study, 1987–1998. Am J Epidemiol. 2002;155:38–47. doi: 10.1093/aje/155.1.38. [DOI] [PubMed] [Google Scholar]
- Chen HC, Chou FH, Chen MC, Su SF, Wang SY, Feng WW, Chen PC, Lai JY, Chao SS, Yang SL, Tsai TC, Tsai KY, Lin KS, Lee CY, Wu HC. A survey of quality of life and depression for police officers in Kaohsiung, Taiwan. Qual Life Res. 2006;15:925–932. doi: 10.1007/s11136-005-4829-9. [DOI] [PubMed] [Google Scholar]
- Ferrieres J, Elias A, Ruidavets JB, Cantet C, Bongard V, Fauvel J, Boccalon H. Carotid intima-media thickness and coronary heart disease risk factors in a low-risk population. J Hyper. 1999;17:743–748. doi: 10.1097/00004872-199917060-00004. [DOI] [PubMed] [Google Scholar]
- Ford ES, Giles WH, Dietz WH. Prevalence of the metabolic syndrome among US adults: findings from the third national health and nutrition examination survey. JAMA. 2002;287:356–359. doi: 10.1001/jama.287.3.356. [DOI] [PubMed] [Google Scholar]
- Franke WD, Anderson DF. Relationship between physical activity and risk factors for cardiovascular disease among law enforcement officers. J Occup Med. 1994;36:1127–1132. doi: 10.1097/00043764-199410000-00016. [DOI] [PubMed] [Google Scholar]
- Franke WD, Collins SA, Hinz PN. Cardiovascular disease morbidity in an Iowa law enforcement cohort, compared with the general Iowa population. J Occup Environ Med. 1998;40:441–444. doi: 10.1097/00043764-199805000-00006. [DOI] [PubMed] [Google Scholar]
- Grobbee DE, Bots ML. Carotid artery intima-media thickness as an indicator of generalized atherosclerosis. J Int Med. 1994;236:567–573. doi: 10.1111/j.1365-2796.1994.tb00847.x. [DOI] [PubMed] [Google Scholar]
- Grundy SM, Cleeman JI, Daniels SR, Donato KA, Eckel RH, Franklin BA, Gordon DJ, Krauss RM, Savage PJ, Smith SC, Jr, Spertus JA, Costa F. American Heart Association; National Heart, Lung, and Blood Institute. Diagnosis and management of the metabolic syndrome: an American Heart Association/National Heart, Lung, and Blood Institute Scientific Statement. Circulation. 2005;112:2735–2752. doi: 10.1161/CIRCULATIONAHA.105.169404. [DOI] [PubMed] [Google Scholar]
- Haas DC, Davidson KW, Schwartz DJ, Riekmann N, Roman MJ, Pickering TG, Gerin W, Schartz JE. Depressive symptoms are independently predictive of carotid atherosclerosis. Am J Cardiol. 2005;95:547–550. doi: 10.1016/j.amjcard.2004.10.032. [DOI] [PubMed] [Google Scholar]
- Howard GA, Sharrett R, Heiss G, Evans GW, Chambless LE, Riley WA, Burke GL. Carotid artery intimal-medial thickness distribution in general populations as evaluated by B-mode ultrasound: ARIC investigators. Stroke. 1993;24:1297–1304. doi: 10.1161/01.str.24.9.1297. [DOI] [PubMed] [Google Scholar]
- Jonas BS, Lando JF. Negative affect as a prospective risk factor for hypertension. Psychosom Med. 2000;62:188–196. doi: 10.1097/00006842-200003000-00006. [DOI] [PubMed] [Google Scholar]
- Jonas BS, Franks P, Ingram DD. Are symptoms of anxiety and depression risk factors for hypertension? Arch Family Med. 1997;6:43–49. doi: 10.1001/archfami.6.1.43. [DOI] [PubMed] [Google Scholar]
- Joseph PN, Violanti JM, Donahue R, Andrew ME, Trevisan M, Burchfiel CM, Dorn J. Police work and subclinical atherosclerosis. J Occup Environ Med. 2009;51:700–707. doi: 10.1097/jom.0b013e3181a02252. [DOI] [PubMed] [Google Scholar]
- Julius S. Transition from high cardiac output to elevated vascular resistance in hypertension. Am Heart J. 1988;116:600–606. doi: 10.1016/0002-8703(88)90557-1. [DOI] [PubMed] [Google Scholar]
- Karlsson B, Knutsson A, Lindahl B. Is there an association between shift work and having a metabolic syndrome? Results from a population based study of 27,485 people. Occup Environ Med. 2001;58:747–752. doi: 10.1136/oem.58.11.747. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Knutson KL, Rathouz PJ, Yan LL, Liu K, Lauderdale DS. Stability of the Pittsburgh sleep quality index and the Epworth sleepiness questionnaires over 1 year in early middle-aged adults: the CARDIA study. Sleep. 2006;29:1503–1506. doi: 10.1093/sleep/29.11.1503. [DOI] [PubMed] [Google Scholar]
- Kop N, Euwema MC. Occupational stress and the use of force by Dutch police officers. Crim Just Beh. 2001;28:631–652. [Google Scholar]
- Lasfargues G, Sylvanie V, Caces B. Relations among night work, dietary habits, biological measures, and health status. Intl J Behav Med. 1996;(3):123–134. doi: 10.1207/s15327558ijbm0302_3. [DOI] [PubMed] [Google Scholar]
- Lorenz MW, Markus HS, Bots ML, Rosvall M, Sitzer M. Prediction of clinical cardiovascular events with carotid intima-media thickness: a systematic review and meta-analysis. Circulation. 2007;115:459–467. doi: 10.1161/CIRCULATIONAHA.106.628875. [DOI] [PubMed] [Google Scholar]
- Musselman DL, Evans DL, Nemeroff CB. The relationship of depression to cardiovascular disease. Arch Gen Psychiatry. 1998a;55:580–592. doi: 10.1001/archpsyc.55.7.580. [DOI] [PubMed] [Google Scholar]
- Musselman DL, Knight BT, Baron A, Nemeroff CB. Presented at society of biological psychiatry annual meeting. Toronto, Canada: 1998b. May, Further studies on altered platelet reactivity in major depression; pp. 27–31. [Google Scholar]
- Nagaya T, Yoshida H, Takahashi H, Kawai M. Markers of insulin resistance in day and shift workers aged 30–59 years. Int Arch Occup Environ Health. 2002;75:562–568. doi: 10.1007/s00420-002-0370-0. [DOI] [PubMed] [Google Scholar]
- Patterson GT. Examining the effects of coping and social support on work and life stress among police officers. J Crim Just. 2003;31:215–226. [Google Scholar]
- Pizzi C, Manzoli L, Mancini S, Bedetti G, Fontana F, Costa GM. Autonomic nervous system, inflammation and preclinical carotid atherosclerosis in depressed subjects with coronary risk factors. Atherosclerosis. 2010;212:292–298. doi: 10.1016/j.atherosclerosis.2010.04.038. [DOI] [PubMed] [Google Scholar]
- Price CS, Pollock ML, Gettman LR, Kent DA. Physical fitness programs for law enforcement officers: a manual for police administrators. Washington, DC: US Department of Justice; 1978. [Google Scholar]
- Radloff LS. The CES-D scale: a self-report depression scale for research in the general population. Appl Psychol Meas. 1977;1:385–401. [Google Scholar]
- Rice SC, Zonderman AB, Metter EJ, Najjoar SS, Waldstein SR. Absence of relation between depressive symptoms and carotid intimal medial thickness in the Blatomire Longitudinal study of aging. Psychosom Med. 2009;71:70–76. doi: 10.1097/PSY.0b013e3181865f73. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Riley WA. Carotid intima-media thickness: risk assessment and scanning protocol. Eur Heart J. 2002;23:916–918. doi: 10.1053/euhj.2001.3122. [DOI] [PubMed] [Google Scholar]
- Sallis JF, Haskell WL, Fortmann SP, Wood PD, Vranizan KM. Moderate-intensity physical activity and cardiovascular risk factors: the Stanford five-city project. Prev Med. 1986;15:561–568. doi: 10.1016/0091-7435(86)90061-7. [DOI] [PubMed] [Google Scholar]
- SAS Institute Inc. SAS/STAT 9.2 User’s Guide. 2008 [Google Scholar]
- Spielberger C, Grier K, Greenfield G. Major dimensions of stress in law enforcement. Florida Fraternal Order Police J Spring. 1982;6:10–20. [Google Scholar]
- Steinhardt M, Greehow L, Stewart The relationship of physical activity and cardiovascular fitness to absenteeism and medical care claims among law enforcement officers. Am J Health Prom. 1991;5:455–460. doi: 10.4278/0890-1171-5.6.455. [DOI] [PubMed] [Google Scholar]
- Stewart JC, Janicki DL, Muldoon MF, Sutoon-Tyrell K, Kamarck TW. Negative emotions and 3-year progression of subclinical atherosclerosis. Arch Gen Psychiatry. 2007;64:225–233. doi: 10.1001/archpsyc.64.2.225. [DOI] [PubMed] [Google Scholar]
- Veith RC, Lewis N, Linares OA, Barnes RF, Raskind MA, Villacres EC, Murburg MM, Ashleigh A, Castillo S, Peskind ER, Pascualy M, Halter JB. Sympathetic nervous system activity in major depression: basal and desipramine-induced alterations in plasma norepinephrine kinetics. Arch Gen Psychiatry. 1994;51:411–422. doi: 10.1001/archpsyc.1994.03950050071008. [DOI] [PubMed] [Google Scholar]
- Violanti JM, Aron F. Ranking police stressors. Psychol Rep. 1994;75:824–826. doi: 10.2466/pr0.1994.75.2.824. [DOI] [PubMed] [Google Scholar]
- Violanti JM, Vena JE, Petralia S. Mortality of a police cohort: 1950–1990. Am J Ind Med. 1998;33:366–373. doi: 10.1002/(sici)1097-0274(199804)33:4<366::aid-ajim6>3.0.co;2-s. [DOI] [PubMed] [Google Scholar]
- Violanti JM, Vena JE, Burchfiel CM, Sharp DS, Miller DB, Andrew ME, Dorn J, Wende-Wactaski J, Beighley CM, Pierino K, Joseph PN, Trevesan M. The Buffalo Cardio-metabolic occupational police stress (BCOPS) pilot study: design, methods, and measurement. Ann Epidemiol. 2006;16:48–156. doi: 10.1016/j.annepidem.2005.07.054. [DOI] [PubMed] [Google Scholar]
- Violanti JM, Burchfiel CM, Hartley TA, Mnatsakanova A, Fekedu-legn D, Andrew ME, Charles LE, Vila BJ. Atypical work hours and metabolic syndrome among police officers. 2009 doi: 10.1080/19338240903241259. [DOI] [PubMed] [Google Scholar]
- Waked EG, Jutai JW. Baseline and reactivity measures of blood pressure and negative affect in borderline hypertension. Physiol Beh. 1990;47:265–271. doi: 10.1016/0031-9384(90)90141-p. [DOI] [PubMed] [Google Scholar]
- Wang Z, Inslicht SS, Metzler TJ, Henn-Haase C, McCaslin SE, Tong H, Neylan TC, Marmer CR. A prospective study of predictor of depression in police. Psychiatry Res. 2010;175:211–216. doi: 10.1016/j.psychres.2008.11.010. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Whipple MO, Lewis TT, Sutton-Tyrell K, Matthews KA, Barinas-Mitchell E, Powell LH, Everson-Rose SA. Hopelessness depressive symptoms, and carotid atherosclerosis in women: the study of women’s health across the nation (SWAN) heart study. Stroke. 2011;40:3166–3172. doi: 10.1161/STROKEAHA.109.554519. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Williams C. Peacetime combat treating and preventing delayed stress reactions in police officers, in Post-traumatic stress disorders: a handbook for clinicians. In: Williams T, editor. Cincinnati: Ohio Disabled American Veterans; 1987. [Google Scholar]
- Wolk R, Somers VK. Sleep and the metabolic syndrome. Exp Physiol. 2007;92:67–78. doi: 10.1113/expphysiol.2006.033787. [DOI] [PubMed] [Google Scholar]