<!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Archiving and Interchange DTD v1.0 20120330//EN" "JATS-archivearticle1.dtd">
<article xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mml="http://www.w3.org/1998/Math/MathML" article-type="research-article"><?properties manuscript?><front><journal-meta><journal-id journal-id-type="nlm-journal-id">100888872</journal-id><journal-id journal-id-type="pubmed-jr-id">22016</journal-id><journal-id journal-id-type="nlm-ta">Int J Emerg Ment Health</journal-id><journal-id journal-id-type="iso-abbrev">Int J Emerg Ment Health</journal-id><journal-title-group><journal-title>International journal of emergency mental health</journal-title></journal-title-group><issn pub-type="ppub">1522-4821</issn></journal-meta><article-meta><article-id pub-id-type="pmid">22900455</article-id><article-id pub-id-type="pmc">4734372</article-id><article-id pub-id-type="manuscript">HHSPA742875</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title-group><article-title>Health Disparities in Police Officers: Comparisons to the U.S. General Population</article-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>Hartley</surname><given-names>Tara A.</given-names></name><aff id="A1">Biostatistics and Epidemiology Branch, Health Effects Laboratory Division, National Institute for Occupational Safety and Health</aff></contrib><contrib contrib-type="author"><name><surname>Burchfiel</surname><given-names>Cecil M.</given-names></name><aff id="A2">Biostatistics and Epidemiology Branch, Health Effects Laboratory Division, National Institute for Occupational Safety and Health</aff></contrib><contrib contrib-type="author"><name><surname>Fekedulegn</surname><given-names>Desta</given-names></name><aff id="A3">Biostatistics and Epidemiology Branch, Health Effects Laboratory Division, National Institute for Occupational Safety and Health</aff></contrib><contrib contrib-type="author"><name><surname>Andrew</surname><given-names>Michael E.</given-names></name><aff id="A4">Biostatistics and Epidemiology Branch, Health Effects Laboratory Division, National Institute for Occupational Safety and Health</aff></contrib><contrib contrib-type="author"><name><surname>Violanti</surname><given-names>John M.</given-names></name><aff id="A5">Department of Social and Preventive Medicine, School of Public Health and Health Professions, State University of New York at Buffalo</aff></contrib></contrib-group><author-notes><corresp id="cor1">Correspondence regarding this article should be directed to Tara A. Hartley, National Institute for Occupational Safety and Health. <email>THartley@cdc.gov</email></corresp></author-notes><pub-date pub-type="nihms-submitted"><day>26</day><month>1</month><year>2016</year></pub-date><pub-date pub-type="ppub"><year>2011</year></pub-date><pub-date pub-type="pmc-release"><day>01</day><month>2</month><year>2016</year></pub-date><volume>13</volume><issue>4</issue><fpage>211</fpage><lpage>220</lpage><abstract><p id="P1">Police officers have one of the poorest cardiovascular disease (CVD) health profiles of any occupation. The goal of this study was to determine if police officers in the Buffalo Cardio-Metabolic Occupational Police Stress (BCOPS) Study (between 2004 and 2009) had a more adverse CV profile than the general U.S. employed population. Nearly one-half (46.9%) of the officers worked a non-day shift compared to 9% of U.S. workers. The percent of officers with depression was nearly double (12.0% vs. 6.8%) and officers were nearly four times more likely to sleep less than six hours in a 24-hour period than the general population (33.0% vs. 8.0%). A higher percentage of officers were obese (40.5% vs. 32.1%), had the metabolic syndrome (26.7% vs. 18.7%), and had higher mean serum total cholesterol levels (200.8 mg/dL vs. 193.2 mg/dL) than the comparison employed populations. In addition to having higher levels of traditional CVD risk factors, police officers had higher levels of non-traditional CVD risk factors. These findings highlight the need for expanding the definition of a health disparity to include occupation. Future studies should expand this comparison to additional traditional and non-traditional CVD risk factors and to other occupational groups.</p></abstract><kwd-group><kwd>law enforcement</kwd><kwd>cardiovascular disease</kwd><kwd>risk factors</kwd><kwd>health disparity</kwd><kwd>epidemiology</kwd></kwd-group></article-meta></front><body><p id="P2">In the United States, cardiovascular disease (CVD) mortality declined considerably (by 65%) from 1968 to 2006, yet heart disease remains the leading cause of death for adults (<xref rid="R33" ref-type="bibr">National Heart, Lung, and Blood Institute [NHLBI], 2009</xref>). Consistent with this, the prevalence of key CVD risk factors (e.g. obesity, high blood pressure, high cholesterol, and diabetes) have also decreased over time but in more recent years these trends have leveled off or actually reversed (<xref rid="R16" ref-type="bibr">Gregg et al., 2005</xref>). These recent trends can have important implications for the workplace, as heart disease is the third leading activity-limiting chronic condition behind arthritis and back and neck conditions (<xref rid="R33" ref-type="bibr">NHLBI, 2009</xref>).</p><p id="P3">Policing is an occupation that requires unpredictable and stressful bursts of intense and strenuous physical activity, placing high demand on the cardiovascular system (<xref rid="R21" ref-type="bibr">Kales, Tsismenakis, Zhang &#x00026; Soteriades, 2009</xref>). In an earlier study, <xref rid="R48" ref-type="bibr">Vena and colleagues (1986)</xref> found that white male police officers died on average seven years earlier than the general U.S. white male population (<xref rid="R1" ref-type="bibr">Arias, 2010</xref>). This finding led to numerous subsequent studies to identify specific risk factors and conditions for this disparity. Police officers exhibit some of the poorest CVD health profiles of any occupation, including higher rates of CVD risk factors (<xref rid="R13" ref-type="bibr">Franke, Ramey &#x00026; Shelley, 2002</xref>; <xref rid="R39" ref-type="bibr">Ramey, Downing, &#x00026; Franke, 2009</xref>; <xref rid="R18" ref-type="bibr">Hartley et al., 2011</xref>; <xref rid="R40" ref-type="bibr">Ramey, Perkhounkova, Downing &#x00026; Culp, 2011</xref>; <xref rid="R50" ref-type="bibr">Wright, Barbosa-Leiker, &#x00026; Hoekstra, 2011</xref>), overt CVD (<xref rid="R13" ref-type="bibr">Franke et al., 2002</xref>; <xref rid="R39" ref-type="bibr">Ramey et al., 2009</xref>), and on-duty CVD events (<xref rid="R21" ref-type="bibr">Kales et al., 2009</xref>).</p><p id="P4">Compounding this issue is the well-known fact that police officers experience high levels of job-related stress, frequently attributed to shift work, the potential for witnessing or experiencing violent events, and organizational pressure (<xref rid="R7" ref-type="bibr">Chen et al., 2006</xref>; <xref rid="R13" ref-type="bibr">Franke et al. 2002</xref>; <xref rid="R15" ref-type="bibr">Gershon, Lin &#x00026; Li, 2002</xref>; <xref rid="R21" ref-type="bibr">Kales et al., 2009</xref>). The effects of job stress are well studied and include increased levels of psychological disorders such as anxiety, depression, and post-traumatic stress disorder (<xref rid="R15" ref-type="bibr">Gershon et al., 2002</xref>), and physiological conditions including hypertension (<xref rid="R13" ref-type="bibr">Franke et al., 2002</xref>; <xref rid="R37" ref-type="bibr">Ramey, 2003</xref>), and CVD (<xref rid="R2" ref-type="bibr">Backe, Seidler, Latza, Rossnagel &#x00026; Schumann, 2011</xref>).</p><p id="P5">A health disparity is a &#x0201c;chain of events signified by a difference in environment, access to, utilization of, and quality of care, health status or a particular health outcome that deserves scrutiny&#x0201d; (<xref rid="R5" ref-type="bibr">Carter-Pokras &#x00026; Baquet, 2002</xref>, p. 427). Health disparities are generally thought of as existing in differing groups, such as racial/ethnic groups, between men and women, or within social classes. However, health disparities may also exist in groups that are strongly influenced by the context of their occupation. This paper compares data on health disparities between participants in an epidemiologic study of police officers from a large Northeastern city with similar estimates from large epidemiologic population-based studies of primarily U.S. employed adults. The goal of this analysis is to determine if this cohort of police officers has a more adverse cardiovascular profile than the general U.S. employed population.</p><sec sec-type="methods" id="S1"><title>METHOD</title><sec id="S2"><title>Study Population</title><p id="P6">Data for the police officers came from the Buffalo Cardio-Metabolic Occupational Police Stress (BCOPS) Study conducted between 2004 and 2009. The overall objective of this cross-sectional study was to examine the association between psychological stress and subclinical CVD among 464 police officers. Each reported value for the variables of interest are taken or derived from findings in published manuscripts from the BCOPS Study (<xref rid="R18" ref-type="bibr">Hartley et al., 2011</xref>; <xref rid="R24" ref-type="bibr">Ma et al., 2011</xref>; <xref rid="R19" ref-type="bibr">Hartley et al., 2012</xref>; <xref rid="R42" ref-type="bibr">Slaven et al., 2012</xref>). All four studies excluded from the analyses 33 retired police officers who participated in the BCOPS Study.</p><p id="P7">Values for each of the variables of interest were obtained from peer-reviewed publications or from data available in U.S. Government reports or Web sites. Data for the general population estimates are primarily from large epidemiological studies of U.S. adults, including the U.S. Centers for Disease Control and Prevention&#x02019;s National Health and Nutrition Examination Survey (NHANES) and the National Health Interview Survey (NHIS), the U.S. Bureau for Labor Statistics&#x02019; Current Population Survey (CPS), and the Multi-Ethnic Study of Atherosclerosis (MESA). For most of these study populations it was possible to restrict the comparison to employed adults (<xref rid="R26" ref-type="bibr">McMenamin, 2007</xref>; <xref rid="R9" ref-type="bibr">Davila et al., 2010</xref>; <xref rid="R43" ref-type="bibr">U.S. Bureau for Labor Statistics, 2011</xref>; <xref rid="R14" ref-type="bibr">Fujishiro et al., 2011</xref>). The estimates for depression and glucose intolerance are from U.S. adult populations not restricted by employment status (<xref rid="R11" ref-type="bibr">Ervin, 2009</xref>; <xref rid="R45" ref-type="bibr">U.S. Centers for Disease Control and Prevention, 2011</xref>). <xref ref-type="table" rid="T1">Table 1</xref> describes these comparison studies and study populations by variable of interest.</p></sec><sec id="S3"><title>Study Measures</title><sec id="S4"><title>Demographics</title><p id="P8">Sex and ethnicity were obtained from a self-reported demographics questionnaire for the BCOPS Study (<xref rid="R18" ref-type="bibr">Hartley et al., 2011</xref>) and from the 2010 U.S. Bureau for Labor Statistics Current Population Survey for the general U.S. employed population (<xref rid="R44" ref-type="bibr">U.S. Census Bureau, 2006</xref>). The percent of women in each study is reported with the corresponding variable of interest. The mean age of the participants in each study is also reported. <xref rid="R14" ref-type="bibr">Fujishiro and colleagues (2011)</xref> reported the mean age using data from employed participants in the MESA Study. For the remaining studies, age was reported by categories and the mean age for these studies was calculated using a weighted average. An upper age limit of 85 was assumed for data from the NHIS and NHANES except for <xref rid="R11" ref-type="bibr">Ervin (2009)</xref> where 59 was the upper limit. The upper age limit of 75 was assumed for data from the Current Population Survey.</p></sec><sec id="S5"><title>Shift Type</title><p id="P9">For the BCOPS Study participants, daily payroll records were obtained from 1994 to date of examination (between 2004 and 2009) and used to calculate the shift most frequently worked (day, afternoon, midnight). A detailed description of the methods used to determine the most frequently worked shift has been reported (<xref rid="R24" ref-type="bibr">Ma et al., 2011</xref>). Shift type was determined for the employed comparison population using questions from the 2004 U.S. Bureau for Labor Statistics&#x02019; Current Population Survey (<xref rid="R26" ref-type="bibr">McMenamin, 2007</xref>) as this was the most recent year available.</p></sec><sec id="S6"><title>Psychosocial Measures</title><p id="P10">Depressive symptoms were measured in the BCOPS Study using the Center for Epidemiologic Sudies--Depression (CES-D) Scale. Details of the CES-D are reported (<xref rid="R36" ref-type="bibr">Radloff, 1977</xref>, <xref rid="R42" ref-type="bibr">Slaven, et al., 2012</xref>). For this study, a cutoff score of 16 or higher was used to identify officers with depression (<xref rid="R36" ref-type="bibr">Radloff, 1977</xref>). For the comparison population, depressive symptoms were measured using the Patient Health Question-naire-9 (PHQ-9) (<xref rid="R45" ref-type="bibr">CDC, 2011</xref>) and for this study a cutoff score of 10 or greater was used to identify participants with depression (<xref rid="R22" ref-type="bibr">Kroenke, Spitzer, &#x00026; Williams, 2001</xref>).</p></sec><sec id="S7"><title>Lifestyle Behaviors</title><p id="P11">For both groups, smoking status was derived from self-reported questionnaires and participants were classified as never smokers, former smokers, or current smokers. Hours of sleep was defined for the BCOPS Study participants using the Pittsburgh Sleep Quality Index (PSQI) question &#x0201c;During the past month, how many hours of actual sleep did you get at night?&#x0201d; (<xref rid="R42" ref-type="bibr">Slaven et al., 2012</xref>). For the comparison population, participants responded to the question &#x0201c;On average, how many hours of sleep do you get in a 24-hour period?&#x0201d; (<xref rid="R23" ref-type="bibr">Luckhaupt, Tak, &#x00026; Calvert, 2010</xref>).</p></sec><sec id="S8"><title>Cardiometabolic Risk Factors</title><p id="P12">Cardiometabolic risk factors (i.e. body mass index, total serum cholesterol, blood pressure, glucose intolerance, metabolic syndrome, common carotid intima media thickness) were obtained using the same procedures for the BCOPS Study participants (<xref rid="R18" ref-type="bibr">Hartley et al., 2011</xref>; <xref rid="R19" ref-type="bibr">Hartley et al., 2012</xref>) and the comparison participants (<xref rid="R11" ref-type="bibr">Ervin, 2009</xref>; <xref rid="R9" ref-type="bibr">Davila et al., 2010</xref>; <xref rid="R14" ref-type="bibr">Fujishiro et al., 2011</xref>). Body mass index (BMI) was used to define the percent of participants who were overweight or obese; a BMI between 25 and 29.9 kg/ m2 is considered overweight and a BMI of 30 kg/m2 or greater is considered obese. Total serum cholesterol levels (mg/dL) were obtained from a 12-hour fasting blood sample. Resting systolic blood pressure was measured three times with a standard sphygmomanometer and reported values are the average of the second and third readings. Glucose intolerance was defined as a fasting serum glucose level of 100 mg/dL or greater, or self-reported diabetes and taking hypoglycemic medication.</p><p id="P13">The metabolic syndrome (MetSyn) was defined using the modified version of the 2001 Third Report of the National Cholesterol Education Program Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (<xref rid="R17" ref-type="bibr">Grundy et al., 2005</xref>). MetSyn was considered present in individuals with 3 or more of the following components: hypertension, reduced high density lipoprotein cholesterol, abdominal obesity, glucose intolerance or hypertriglyceridemia.</p><p id="P14">Common carotid intima media thickness (IMT) measurements were obtained via ultrasound scans using standardized protocols. Details of the scan have been previously reported (<xref rid="R14" ref-type="bibr">Fujishiro et al., 2011</xref>; <xref rid="R18" ref-type="bibr">Hartley et al., 2011</xref>). Briefly, standardized longitudinal images were acquired of the near and far walls of the distal 10 mm portion of the common carotid artery (CCA) on both the right and left sides.</p></sec></sec></sec><sec sec-type="results" id="S9"><title>RESULTS</title><p id="P15">The comparison between the BCOPS Study participants and the general U.S. employed population can be found in <xref ref-type="table" rid="T2">Table 2</xref>. In general, just over 25% of the BCOPS Study participants were women (range 25.9% - 28.6%) compared to nearly 50% of the comparison study participants (range 42.4% - 50.6%). The mean age for the BCOPS Study participants across the studies was approximately 41 years (range 40.7 &#x02013; 41.5). There was considerable variation in the mean age for the comparison study participants. The weighted mean age ranged from 39.5 years for the 2003 &#x02013; 2006 NHANES population to 56.4 years for the employed participants of the MESA Study.</p><p id="P16">Focusing on the specific variables of interest, slightly more than one-quarter of the BCOPS Study participants were women compared to 42% of U.S. workers. Twenty percent of the officers were black compared to only 11% of U.S. workers; only 1.8% of officers were Hispanic compared to 14.3% of U.S. workers. Nearly one-half (46.9%) of the police officers worked a non-day shift compared to 9% of U.S. workers. The percent of officers with depression (police officers: CES-D &#x02265; 16; comparison group: PHQ-9 &#x02265; 10) was nearly double that of the general population (12.0% vs. 6.8%).</p><p id="P17">A slightly higher percent of officers were current smokers compared to the employed population (16.7% vs. 13.6%). Police officers were four times more likely to sleep less than six hours in a 24-hour period than the employed population (33.0% vs. 8.0%). The percentage of officers who were overweight was similar to the employed population (41.5% vs. 40.0%); the percent obese was higher for the officers compared to the employed population (40.5% vs. 32.1%).</p><p id="P18">Mean serum total cholesterol levels were slightly higher for officers compared to the employed population (200.8 mg/ dL vs. 193.2 mg/dL), while systolic blood pressure levels were similar for both groups (120.9 mm Hg, 121.6 mm Hg, respectively). The percent of police officers who were glucose intolerant was lower than the general population (23.6% vs. 32.4%). However, nearly 27% of police officers had MetSyn, which includes glucose intolerance and hypertension, compared to 18.7% of the employed population. The mean common carotid intima media thickness for the police officers was 0.62 mm compared to 0.82 mm for the employed population.</p></sec><sec sec-type="conclusions" id="S10"><title>CONCLUSIONS</title><p id="P19">In the current study we compared levels of traditional and non-traditional CVD risk factors between participants in the BCOPS Study with estimates from the general U.S. employed population. Nearly three-quarters of the police officers were men compared to about 58% of U.S. workers. This discrepancy was consistent throughout each of the comparisons of the variables of interest. Policing is a male dominated occupation where women account for just over 10% of all sworn law enforcement personnel in the U.S. (<xref rid="R31" ref-type="bibr">National Center for Women and Policing, 2002</xref>). Ethnicity also varied between the two groups. Just over 20% of police officers were black compared to 11% of all U.S. workers. There were a very small percentage of Hispanic police officers compared to 14% of U.S. workers.</p><p id="P20">Nearly half of the police officers worked a non-day shift compared to less than 10% of the U.S. workforce. Policing is a 24-hour occupation and shift work is a necessity. However, night shift work can have considerable consequences on health and safety. Shift work has been associated with CVD, obesity, MetSyn, diabetes, and mood and anxiety disorders, most likely as a result of circadian rhythm disruption (<xref rid="R41" ref-type="bibr">Shift work and sleep, 2011</xref>).</p><p id="P21">One-third of police officers reported sleeping less than six hours in a 24-hour period; this finding was four times higher than employed workers completing the National Health Interview Survey. Sleep loss can be a consequence of shift work, and has been associated with higher levels of perceived stress in male police officers and among those with higher police ranks and greater workloads (Charles et al., 2012). Chronic sleep loss can lead to excessive fatigue and impaired alertness. These outcomes can have immediate consequences for police officers as the nature of their job requires them to function in a hypervigilant state (<xref rid="R41" ref-type="bibr">Shift work and sleep, 2011</xref>).</p><p id="P22">The prevalence of depression was nearly twice as high for the police officers as the general population. This finding is somewhat surprising given that the comparison study sample was not restricted to employed adults, included a higher percentage of women, and possibly included a higher percentage of persons who have chronic medical conditions and those who are unemployed. Depression is known to be higher among women, those with chronic medical conditions, and those who are unemployed (<xref rid="R25" ref-type="bibr">Marcotte, Wilcox-Gok, &#x00026; Redmon, 1999</xref>; National Institute of Mental Health; <xref rid="R47" ref-type="bibr">U.S. Department of Health and Human Services, 1999</xref>). However, age is also a significant risk factor for depression. According to the National Health Statistics Report (<xref rid="R35" ref-type="bibr">Pratt &#x00026; Brody, 2008</xref>), persons between 40&#x02013;59 years of age have the highest prevalence of depression compared to teens, young adults, and older adults. Roughly 60% of the BCOPS Study participants fall into this working age category (<xref rid="R18" ref-type="bibr">Hartley et al., 2011</xref>). Workers in this age category may also be providing child care and/or elder care in addition to their responsibilities as a police officer. And as previously indicated, policing itself is considered to be a high stress occupation (<xref rid="R15" ref-type="bibr">Gershon et al., 2002</xref>) and job strain and low social support at work have been significantly associated with major depressive disorder (MDD; <xref rid="R4" ref-type="bibr">Blackmore et al., 2007</xref>).</p><p id="P23">With regard to the cardio-metabolic risk factors, police officers had a similar percentage of participants who were overweight (BMI 25&#x02013;30 kg/m2), similar levels of systolic blood pressure, and lower levels of glucose intolerance compared to the respective comparison population. Yet the prevalence of MetSyn, which includes these three risk factors in addition to hypertriglyceridemia and reduced HDL-C, was approximately 8% higher for police officers than workers in the comparison study. The MetSyn component hypertension includes three items: systolic blood pressure &#x02265; 130 mm Hg, diastolic blood pressure &#x02265; 85 mm Hg, and antihypertensive treatment. Relying solely on systolic blood pressure levels may represent an underestimation of hypertension as successful treatment for hypertension should reduce levels of systolic blood pressure. As we have reported, the MetSyn component hypertension is high among these police officers with 39% meeting at least one of the three component criteria (<xref rid="R18" ref-type="bibr">Hartley et al., 2011</xref>; <xref rid="R19" ref-type="bibr">Hartley et al., 2012</xref>).</p><p id="P24">The percentage of officers currently smoking was 3.1% higher at 16.7%, obesity was 8.4% higher at 40.5%, and the serum total cholesterol levels were approximately 7.6 mg/ dL higher at 200.8 mg/dL, than the employed MESA Study participants. These values for the police officers fall well short of the U.S. Healthy People 2010 recommendations: reduction in mean total blood cholesterol to 199 mg/dL, smoking to 12% of the population, and obesity to 15% of the population (<xref rid="R46" ref-type="bibr">U.S. Department of Health and Human Services, 2000</xref>). The higher values are not entirely attributable to age as the mean age of the police officers is notably 15 years younger than the employed comparison study participants. This makes these differences more striking given that obesity and total cholesterol typically increase from young adulthood to retirement age (<xref rid="R29" ref-type="bibr">Mizuno, Shu, Makimura &#x00026; Mobbs, 2004</xref>; <xref rid="R30" ref-type="bibr">National Center for Health Statistics, 2009</xref>) and are often higher in women than in men regardless of ethnicity or educational level (<xref rid="R27" ref-type="bibr">Mensah, Mokdad, Ford, Greenlund &#x00026; Croft, 2005</xref>; <xref rid="R49" ref-type="bibr">Wang &#x00026; Beydoun, 2007</xref>). One possible explanation for these differences is that police officers spend a considerable amount of on-duty time being relatively inactive (<xref rid="R21" ref-type="bibr">Kales et al., 2009</xref>) and physical inactivity is a risk factor for both obesity and hypercholesterolemia (<xref rid="R34" ref-type="bibr">Pate et al., 1995</xref>).</p><p id="P25">Common carotid IMT values were much lower for police officers compared to the employed MESA Study participants. This finding is somewhat surprising given the difference in the percentage of women between the BCOPS Study and the MESA Study participants (25.9% vs. 46.9%, respectively). Women typically have lower carotid IMT than men (<xref rid="R20" ref-type="bibr">Howard et al., 1993</xref>; <xref rid="R18" ref-type="bibr">Hartley et al., 2011</xref>). However, the BCOPS Study participants were about 15 years younger than the MESA Study participants which may explain most of the difference between the two groups; carotid IMT increases at approximately 0.01 mm per year (<xref rid="R20" ref-type="bibr">Howard et al., 1993</xref>).</p><p id="P26">Previous studies have found police officers to have higher rates of CVD risk factors and CVD morbidity than other groups (<xref rid="R13" ref-type="bibr">Franke et al., 2002</xref>; <xref rid="R39" ref-type="bibr">Ramey et al., 2009</xref>; <xref rid="R40" ref-type="bibr">Ramey et al., 2011</xref>). In the current study, we compared police officers with reported results from studies including mostly employed adults. Our findings are consistent with those previously reported: a higher percentage of police officers were obese and had the MetSyn. In addition to these more traditional CVD risk factors, we found a higher prevalence of depression, and a higher percentage of police officers who work a non-day shift and sleep less than six hours a night compared to other employed adults. Previous research has reported that police officers are a known high stress occupational group (<xref rid="R8" ref-type="bibr">Collins &#x00026; Gibbs, 2003</xref>) and that the stress associated with policing may predispose officers to higher rates of CVD morbidity and mortality (<xref rid="R12" ref-type="bibr">Franke, Collins &#x00026; Hinz, 1998</xref>). Importantly, stress initiates an inflammatory process that may attribute to the CVD observed in 40% of atherosclerotic patients who lack traditional CVD risk factors (<xref rid="R3" ref-type="bibr">Black &#x00026; Garbutt, 2002</xref>). This pathway may be supported by the findings in the current study.</p><p id="P27">This study has several noteworthy limitations. First, variables were selected based on their availability in published findings. Information on other key demographic variables, lifestyle variables, and CVD risk factors would be beneficial in providing a more comprehensive understanding of the health disparities of police officers. Second, there may be key differences in the demographic profile of the BCOPS Study participants and each of the comparison groups. The comparison groups were carefully selected based on the following criteria: 1) publication of findings in the scientific literature, 2) studies were conducted in the United States, 3) study participants were adults (&#x02265; 18 or &#x02265; 20, depending upon the individual study), and 4) study participants were employed. Percentage of women and mean age (actual or calculated from weighted averages) were reported and, where appropriate, were considered as a potential explanation for differences between the two groups. Third, CVD risk factors may differ by demographic characteristics. For example, in our previous findings, male police officers were found to have a higher prevalence of MetSyn than female police officers (<xref rid="R18" ref-type="bibr">Hartley et al., 2011</xref>). Yet, in the current study we were not able to stratify the analyses by key demographic characteristics, such as sex and age. Finally, several of the variables used in the comparison were derived from different measures. For example, the prevalence of depression is based on the Center for Epidemiologic Studies &#x02013; Depression Scale (CES-D) for the BCOPS Study participants and from the Patient Health Questionnaire-9 (PHQ-9) for the comparison group, which may represent one potential explanation for the difference found between the two groups, although the level of agreement between the two measures has been addressed by others (<xref rid="R10" ref-type="bibr">Dbouk, Arguedas, &#x00026; Sheikh, 2008</xref>; <xref rid="R28" ref-type="bibr">Milette, Hudon, Baron, Thombs &#x00026; Canadian Scleroderma Research Group, 2010</xref>).</p><p id="P28">Strengths of this study include the use of clinical measurements versus self-report. Previous studies comparing police officers with the general population have relied upon self-report measures of hypertension, hypercholesterolemia and diabetes (<xref rid="R38" ref-type="bibr">Ramey, Downing &#x00026; Knoblauch, 2008</xref>). In the current study, all six of the cardio-metabolic risk factors were obtained via standardized anthropometric and clinical protocols for both the BCOPS Study participants and the respective comparison groups, thus eliminating concerns about reporting bias.</p><p id="P29">In the current study we found that police officers have higher levels of traditional and non-traditional CVD risk factors than other employed adults. To our knowledge this is the first comparison of key CVD risk factors between a sample of police officers and the general U.S. employed population. Our findings highlight the need for expanding the scope of demographic characteristics that define a health disparity to include occupation, as this factor can contribute significantly to an individual&#x02019;s overall health and well-being. Future studies should reexamine this comparison with additional traditional and non-traditional CVD risk factors and should be expanded to other occupational groups.</p></sec></body><back><ack id="S11"><p id="P30">This work was supported by the National Institute for Occupational Safety and Health contract number 200-2003-01580.</p></ack><fn-group><fn id="FN1"><p id="P31">Disclaimer: The findings and conclusions in this report are those of the authors and do not necessarily represent the views of the National Institute for Occupational Safety and Health.</p></fn></fn-group><ref-list><title>REFERENCES</title><ref id="R1"><element-citation publication-type="book"><person-group person-group-type="author"><name><surname>Arias</surname><given-names>E</given-names></name></person-group><source>United States life tables, 2006. (National Vital Statistics Reports, Vol. 58, No. 21)</source><year>2010</year><publisher-loc>Hyattsville, MD</publisher-loc><publisher-name>National Center for Health Statistics</publisher-name></element-citation></ref><ref id="R2"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Backe</surname><given-names>E</given-names></name><name><surname>Seidler</surname><given-names>A</given-names></name><name><surname>Latza</surname><given-names>U</given-names></name><name><surname>Rossnagel</surname><given-names>K</given-names></name><name><surname>Schumann</surname><given-names>B</given-names></name></person-group><article-title>The role of psychosocial stress at work for the development of cardiovascular diseases: A systematic review</article-title><source>International Archives of Occupational and Environmental Health</source><year>2011</year><comment>Epub ahead of print</comment></element-citation></ref><ref id="R3"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Black</surname><given-names>PH</given-names></name><name><surname>Garbutt</surname><given-names>LD</given-names></name></person-group><article-title>Stress, inflammation and cardiovascular disease</article-title><source>Journal of Psychosomatic Research</source><year>2002</year><volume>52</volume><fpage>1</fpage><lpage>23</lpage><pub-id pub-id-type="pmid">11801260</pub-id></element-citation></ref><ref id="R4"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Blackmore</surname><given-names>ER</given-names></name><name><surname>Stansfeld</surname><given-names>SA</given-names></name><name><surname>Weller</surname><given-names>I</given-names></name><name><surname>Munce</surname><given-names>S</given-names></name><name><surname>Zagorski</surname><given-names>BM</given-names></name><name><surname>Stewart</surname><given-names>DE</given-names></name></person-group><article-title>Major depressive episodes and work stress: Results from a national population survey</article-title><source>American Journal of Public Health</source><year>2007</year><volume>97</volume><fpage>2088</fpage><lpage>2093</lpage><pub-id pub-id-type="pmid">17901431</pub-id></element-citation></ref><ref id="R5"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Carter-Pokras</surname><given-names>O</given-names></name><name><surname>Baquet</surname><given-names>C</given-names></name></person-group><article-title>What is a &#x0201c;health disparity&#x0201d;?</article-title><source>Public Health Reports</source><year>2002</year><volume>117</volume><fpage>426</fpage><lpage>434</lpage><pub-id pub-id-type="pmid">12500958</pub-id></element-citation></ref><ref id="R6"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Charles</surname><given-names>LE</given-names></name><name><surname>Slaven</surname><given-names>JE</given-names></name><name><surname>Mnatsakanova</surname><given-names>A</given-names></name><name><surname>Ma</surname><given-names>C</given-names></name><name><surname>Violanti</surname><given-names>JM</given-names></name><name><surname>Fekedulegn</surname><given-names>D</given-names></name><etal/></person-group><article-title>Associations of perceived stress with sleep duration and sleep quality: The BCOPS Study</article-title><source>International Journal of Emergency Mental Health</source><year>2011</year><volume>13</volume><issue>4</issue><fpage>229</fpage><lpage>242</lpage><pub-id pub-id-type="pmid">22900457</pub-id></element-citation></ref><ref id="R7"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Chen</surname><given-names>H</given-names></name><name><surname>Chou</surname><given-names>FH</given-names></name><name><surname>Chen</surname><given-names>M</given-names></name><name><surname>Su</surname><given-names>S</given-names></name><name><surname>Wang</surname><given-names>S</given-names></name><name><surname>Feng</surname><given-names>W</given-names></name><etal/></person-group><article-title>A survey of quality of life and depression for police officers in Kaohsiung, Taiwan</article-title><source>Quality of Life Research</source><year>2006</year><volume>15</volume><fpage>925</fpage><lpage>932</lpage><pub-id pub-id-type="pmid">16721651</pub-id></element-citation></ref><ref id="R8"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Collins</surname><given-names>PA</given-names></name><name><surname>Gibbs</surname><given-names>ACC</given-names></name></person-group><article-title>Stress in police officers: A study of the origins, prevalence and severity of stress-related symptoms within a county police force</article-title><source>Occupational Medicine</source><year>2003</year><volume>53</volume><fpage>256</fpage><lpage>264</lpage><pub-id pub-id-type="pmid">12815123</pub-id></element-citation></ref><ref id="R9"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Davila</surname><given-names>EP</given-names></name><name><surname>Florez</surname><given-names>H</given-names></name><name><surname>Fleming</surname><given-names>LE</given-names></name><name><surname>Lee</surname><given-names>DJ</given-names></name><name><surname>Goodman</surname><given-names>E</given-names></name><name><surname>LeBlanc</surname><given-names>WG</given-names></name><etal/></person-group><article-title>Prevalence of the metabolic syndrome among U.S. workers</article-title><source>Diabetes Care</source><year>2010</year><volume>33</volume><fpage>2390</fpage><lpage>2395</lpage><pub-id pub-id-type="pmid">20585004</pub-id></element-citation></ref><ref id="R10"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Dbouk</surname><given-names>N</given-names></name><name><surname>Arguedas</surname><given-names>MR</given-names></name><name><surname>Sheikh</surname><given-names>A</given-names></name></person-group><article-title>Assessment of the PHQ-9 as a screening tool for depression in patients with chronic hepatitis C</article-title><source>Digestive Disease Science</source><year>2008</year><volume>53</volume><fpage>1100</fpage><lpage>1106</lpage></element-citation></ref><ref id="R11"><element-citation publication-type="book"><person-group person-group-type="author"><name><surname>Ervin</surname><given-names>RB</given-names></name></person-group><source>Prevalence of metabolic syndrome among adults 20 years of age and over, by sex, age, race and ethnicity, and body mass index: United States, 2003&#x02013;2006 (National Health Statistics Reports No 13)</source><year>2009</year><publisher-loc>Hyattsville, MD</publisher-loc><publisher-name>National Center for Health Statistics</publisher-name></element-citation></ref><ref id="R12"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Franke</surname><given-names>WD</given-names></name><name><surname>Collins</surname><given-names>SA</given-names></name><name><surname>Hinz</surname><given-names>PN</given-names></name></person-group><article-title>Cardiovascular disease morbidity in an Iowa law enforcement cohort, compared with the general Iowa population</article-title><source>Journal of Occupational and Environmental Medicine</source><year>1998</year><volume>40</volume><fpage>441</fpage><lpage>444</lpage><pub-id pub-id-type="pmid">9604181</pub-id></element-citation></ref><ref id="R13"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Franke</surname><given-names>WD</given-names></name><name><surname>Ramey</surname><given-names>SL</given-names></name><name><surname>Shelley</surname><given-names>MC</given-names></name></person-group><article-title>Relationship between cardiovascular disease morbidity, risk factors, and stress in a law enforcement cohort</article-title><source>Journal of Occupational and Environmental Medicine</source><year>2002</year><volume>44</volume><fpage>1182</fpage><lpage>1189</lpage><pub-id pub-id-type="pmid">12500462</pub-id></element-citation></ref><ref id="R14"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Fujishiro</surname><given-names>K</given-names></name><name><surname>Diez Roux</surname><given-names>AV</given-names></name><name><surname>Landsbergis</surname><given-names>P</given-names></name><name><surname>Baron</surname><given-names>S</given-names></name><name><surname>Barr</surname><given-names>RG</given-names></name><name><surname>Kaufman</surname><given-names>JD</given-names></name><etal/></person-group><article-title>Associations of occupation, job control and job demands with intima-media thickness: The Multi-Ethnic Study of Atherosclerosis (MESA)</article-title><source>Occupational and Environmental Medicine</source><year>2011</year><volume>68</volume><fpage>319</fpage><lpage>326</lpage><pub-id pub-id-type="pmid">20935285</pub-id></element-citation></ref><ref id="R15"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Gershon</surname><given-names>RRM</given-names></name><name><surname>Lin</surname><given-names>S</given-names></name><name><surname>Li</surname><given-names>X</given-names></name></person-group><article-title>Work stress in aging police officers</article-title><source>Journal of Occupational and Environmental Medicine</source><year>2002</year><volume>44</volume><fpage>160</fpage><lpage>167</lpage><pub-id pub-id-type="pmid">11851217</pub-id></element-citation></ref><ref id="R16"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Gregg</surname><given-names>EW</given-names></name><name><surname>Cheng</surname><given-names>J</given-names></name><name><surname>Cadwell</surname><given-names>BL</given-names></name><name><surname>Imperatore</surname><given-names>G</given-names></name><name><surname>Williams</surname><given-names>DE</given-names></name><name><surname>Flegal</surname><given-names>KM</given-names></name><etal/></person-group><article-title>Secular trends in cardiovascular disease risk factors according to body mass index in U.S. adults</article-title><source>Journal of the American Medical Association</source><year>2005</year><volume>293</volume><fpage>1868</fpage><lpage>1874</lpage><pub-id pub-id-type="pmid">15840861</pub-id></element-citation></ref><ref id="R17"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Grundy</surname><given-names>SM</given-names></name><name><surname>Cleeman</surname><given-names>JI</given-names></name><name><surname>Daniels</surname><given-names>SR</given-names></name><name><surname>Donato</surname><given-names>KA</given-names></name><name><surname>Eckel</surname><given-names>RH</given-names></name><name><surname>Franklin</surname><given-names>BA</given-names></name><etal/></person-group><article-title>Diagnosis and management of the metabolic syndrome. An American Heart Association/National Heart, Lung, and Blood Institute Scientific Statement</article-title><source>Circulation</source><year>2005</year><volume>112</volume><fpage>2735</fpage><lpage>2752</lpage><pub-id pub-id-type="pmid">16157765</pub-id></element-citation></ref><ref id="R18"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Hartley</surname><given-names>TA</given-names></name><name><surname>Shankar</surname><given-names>A</given-names></name><name><surname>Fekedulegn</surname><given-names>D</given-names></name><name><surname>Violanti</surname><given-names>JM</given-names></name><name><surname>Andrew</surname><given-names>ME</given-names></name><name><surname>Knox</surname><given-names>SS</given-names></name><name><surname>Burchfiel</surname><given-names>CM</given-names></name></person-group><article-title>Metabolic syndrome and carotid intima media thickness in urban police officers</article-title><source>Journal of Occupational and Environmental Medicine</source><year>2011</year><volume>53</volume><fpage>553</fpage><lpage>561</lpage><pub-id pub-id-type="pmid">21505360</pub-id></element-citation></ref><ref id="R19"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Hartley</surname><given-names>TA</given-names></name><name><surname>Burchfiel</surname><given-names>CM</given-names></name><name><surname>Fekedulegn</surname><given-names>D</given-names></name><name><surname>Andrew</surname><given-names>ME</given-names></name><name><surname>Knox</surname><given-names>SS</given-names></name><name><surname>Violanti</surname><given-names>JM</given-names></name></person-group><article-title>Association between police officer stress and the metabolic syndrome</article-title><source>International Journal of Emergency Mental Health</source><year>2012</year><volume>13</volume><issue>4</issue><fpage>243</fpage><lpage>256</lpage><pub-id pub-id-type="pmid">22900458</pub-id></element-citation></ref><ref id="R20"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Howard</surname><given-names>G</given-names></name><name><surname>Sharrett</surname><given-names>AR</given-names></name><name><surname>Heiss</surname><given-names>G</given-names></name><name><surname>Evans</surname><given-names>GW</given-names></name><name><surname>Chambless</surname><given-names>LE</given-names></name><name><surname>Riley</surname><given-names>WA</given-names></name><name><surname>Burke</surname><given-names>GL</given-names></name></person-group><article-title>Carotid artery intimalmedial thickness distribution in general populations as evaluated by B-mode ultrasound. ARIC Investigators</article-title><source>Stroke</source><year>1993</year><volume>24</volume><fpage>1297</fpage><lpage>1304</lpage><pub-id pub-id-type="pmid">8362421</pub-id></element-citation></ref><ref id="R21"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Kales</surname><given-names>SN</given-names></name><name><surname>Tsismenakis</surname><given-names>AJ</given-names></name><name><surname>Zhang</surname><given-names>C</given-names></name><name><surname>Soteriades</surname><given-names>ES</given-names></name></person-group><article-title>Blood pressure in firefighters, police officers, and other emergency responders</article-title><source>American Journal of Hypertension</source><year>2009</year><volume>22</volume><fpage>11</fpage><lpage>20</lpage><pub-id pub-id-type="pmid">18927545</pub-id></element-citation></ref><ref id="R22"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Kroenke</surname><given-names>K</given-names></name><name><surname>Spitzer</surname><given-names>RL</given-names></name><name><surname>Williams</surname><given-names>JBW</given-names></name></person-group><article-title>The PHQ-9: Validity of a brief depression severity measures</article-title><source>Journal of General Internal Medicine</source><year>2001</year><volume>16</volume><fpage>606</fpage><lpage>613</lpage><pub-id pub-id-type="pmid">11556941</pub-id></element-citation></ref><ref id="R23"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Luckhaupt</surname><given-names>SE</given-names></name><name><surname>Tak</surname><given-names>S</given-names></name><name><surname>Calvert</surname><given-names>GM</given-names></name></person-group><article-title>The prevalence of short sleep duration by industry and occupation in the National Health Interview Survey</article-title><source>Sleep</source><year>2010</year><volume>33</volume><fpage>149</fpage><lpage>159</lpage><pub-id pub-id-type="pmid">20175398</pub-id></element-citation></ref><ref id="R24"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Ma</surname><given-names>C</given-names></name><name><surname>Burchfiel</surname><given-names>CM</given-names></name><name><surname>Fekedulegn</surname><given-names>D</given-names></name><name><surname>Andrew</surname><given-names>ME</given-names></name><name><surname>Charles</surname><given-names>LE</given-names></name><name><surname>Gu</surname><given-names>JK</given-names></name><etal/></person-group><article-title>Association of shift work with physical activity among police officers: The Buffalo Cardio-Metabolic Occupational Police Stress Study</article-title><source>Journal of Occupational and Environmental Medicine</source><year>2011</year><volume>53</volume><fpage>1030</fpage><lpage>1036</lpage><pub-id pub-id-type="pmid">21866054</pub-id></element-citation></ref><ref id="R25"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Marcotte</surname><given-names>DE</given-names></name><name><surname>Wilcox-Gok</surname><given-names>V</given-names></name><name><surname>Redmon</surname><given-names>DP</given-names></name></person-group><article-title>Prevalence and patterns of major depressive disorder in the United States labor force</article-title><source>Journal of Mental Health Policy and Economics</source><year>1999</year><volume>2</volume><fpage>123</fpage><lpage>131</lpage><pub-id pub-id-type="pmid">11967420</pub-id></element-citation></ref><ref id="R26"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>McMenamin</surname><given-names>TM</given-names></name></person-group><article-title>A time to work: recent trends in shift work and flexible schedules</article-title><source>Monthly Labor Review</source><year>2007</year><fpage>3</fpage><lpage>15</lpage></element-citation></ref><ref id="R27"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Mensah</surname><given-names>GA</given-names></name><name><surname>Mokdad</surname><given-names>AH</given-names></name><name><surname>Ford</surname><given-names>ES</given-names></name><name><surname>Greenlund</surname><given-names>KJ</given-names></name><name><surname>Croft</surname><given-names>JB</given-names></name></person-group><article-title>States of disparities in cardiovascular health in the United States</article-title><source>Circulation</source><year>2005</year><volume>111</volume><fpage>1233</fpage><lpage>1241</lpage><pub-id pub-id-type="pmid">15769763</pub-id></element-citation></ref><ref id="R28"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Milette</surname><given-names>K</given-names></name><name><surname>Hudson</surname><given-names>M</given-names></name><name><surname>Baron</surname><given-names>M</given-names></name><name><surname>Thombs</surname><given-names>BD</given-names></name></person-group><collab>Canadian Scleroderma Research Group</collab><article-title>Comparison of the PHQ-9 and CES-D depression scales in systemic sclerosis: internal consistency reliability, convergent validity and clinical correlates</article-title><source>Rheumatology</source><year>2010</year><volume>49</volume><fpage>789</fpage><lpage>796</lpage><pub-id pub-id-type="pmid">20100794</pub-id></element-citation></ref><ref id="R29"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Mizuno</surname><given-names>T</given-names></name><name><surname>Shu</surname><given-names>I</given-names></name><name><surname>Makimura</surname><given-names>H</given-names></name><name><surname>Mobbs</surname><given-names>C</given-names></name></person-group><article-title>Obesity over the life course</article-title><source>Science of Aging Knowledge Environment</source><year>2004</year><volume>24</volume><fpage>re4</fpage><lpage>re7</lpage><pub-id pub-id-type="pmid">15201431</pub-id></element-citation></ref><ref id="R30"><element-citation publication-type="gov"><collab>National Center for Health Statistics</collab><source>Health, United States, 2008 with Chartbook</source><year>2009</year><comment>Retrieved from <ext-link ext-link-type="uri" xlink:href="http://www.cdc.gov/nchs/data/hus/hus08.pdf">http://www.cdc.gov/nchs/data/hus/hus08.pdf</ext-link></comment></element-citation></ref><ref id="R31"><element-citation publication-type="book"><collab>National Center for Women and Policing (NCWP)</collab><source>Equality denied: The status of women in policing: 2001</source><year>2002</year><publisher-loc>New York, NY</publisher-loc><publisher-name>Columbia University</publisher-name></element-citation></ref><ref id="R32"><element-citation publication-type="gov"><collab>National Institute of Mental Health</collab><source>Major depressive disorder among adults</source><comment>Retrieved from <ext-link ext-link-type="uri" xlink:href="http://www.nimh.nih.gov/statistics/1MDD_ADULT.shtml">http://www.nimh.nih.gov/statistics/1MDD_ADULT.shtml</ext-link></comment></element-citation></ref><ref id="R33"><element-citation publication-type="gov"><collab>National Heart, Lung, and Blood Institute</collab><source>Morbidity and Mortality: 2009 Chart Book on Cardiovascular, Lung and Blood Disease</source><year>2009</year><comment>Retrieved from <ext-link ext-link-type="uri" xlink:href="http://www.nhlbi.nih.gov/resources/docs/2009_ChartBook.pdf">http://www.nhlbi.nih.gov/resources/docs/2009_ChartBook.pdf</ext-link></comment></element-citation></ref><ref id="R34"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Pate</surname><given-names>RR</given-names></name><name><surname>Pratt</surname><given-names>M</given-names></name><name><surname>Blair</surname><given-names>SN</given-names></name><name><surname>Haskell</surname><given-names>WL</given-names></name><name><surname>Macera</surname><given-names>CA</given-names></name><name><surname>Bouchard</surname><given-names>C</given-names></name><etal/></person-group><article-title>Physical activity and public health: A recommendation from the Centers for Disease Control and Prevention and the American College of Sports Medicine</article-title><source>Journal of the American Medical Association</source><year>1995</year><volume>273</volume><fpage>402</fpage><lpage>407</lpage><pub-id pub-id-type="pmid">7823386</pub-id></element-citation></ref><ref id="R35"><element-citation publication-type="gov"><person-group person-group-type="author"><name><surname>Pratt</surname><given-names>LA</given-names></name><name><surname>Brody</surname><given-names>DJ</given-names></name></person-group><source>Depression in the United States household population, 2005&#x02013;2006. (National Center for Health Statistics No. 7)</source><year>2008</year><comment>Retrieved from <ext-link ext-link-type="uri" xlink:href="http://www.cdc.gov/nchs/data/databriefs/db07.pdf">http://www.cdc.gov/nchs/data/databriefs/db07.pdf</ext-link></comment></element-citation></ref><ref id="R36"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Radloff</surname><given-names>LS</given-names></name></person-group><article-title>The CES-D scale: A self-report depression scale for research in the general population</article-title><source>Applied Psychological Measurement</source><year>1977</year><volume>1</volume><fpage>385</fpage><lpage>401</lpage></element-citation></ref><ref id="R37"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Ramey</surname><given-names>SL</given-names></name></person-group><article-title>Cardiovascular disease risk factors and the perception of general health among male law enforcement officers: Encouraging behavioral change</article-title><source>American Association of Occupational Health Nurses Journal</source><year>2003</year><volume>51</volume><fpage>219</fpage><lpage>226</lpage></element-citation></ref><ref id="R38"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Ramey</surname><given-names>SL</given-names></name><name><surname>Downing</surname><given-names>NR</given-names></name><name><surname>Knoblauch</surname><given-names>A</given-names></name></person-group><article-title>Developing strategic interventions to reduce cardiovascular disease risk among law enforcement officers: The art and science of data triangulation</article-title><source>American Association of Occupational Health Nurses Journal</source><year>2008</year><volume>56</volume><fpage>54</fpage><lpage>62</lpage></element-citation></ref><ref id="R39"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Ramey</surname><given-names>SL</given-names></name><name><surname>Downing</surname><given-names>NR</given-names></name><name><surname>Franke</surname><given-names>WD</given-names></name></person-group><article-title>Milwaukee Police Department retirees: Cardiovascular disease risk and morbidity among aging law enforcement officers</article-title><source>American Association of Occupational Health Nurses Journal</source><year>2009</year><volume>57</volume><fpage>448</fpage><lpage>453</lpage></element-citation></ref><ref id="R40"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Ramey</surname><given-names>SL</given-names></name><name><surname>Perkhounkova</surname><given-names>Y</given-names></name><name><surname>Downing</surname><given-names>NR</given-names></name><name><surname>Culp</surname><given-names>KR</given-names></name></person-group><article-title>Relationship of cardiovascular disease to stress and vital exhaustion in an urban, Midwestern police department</article-title><source>American Association of Occupational Health Nurses Journal</source><year>2011</year><volume>59</volume><fpage>221</fpage><lpage>227</lpage></element-citation></ref><ref id="R41"><element-citation publication-type="journal"><collab>Shift work and sleep: Optimizing health, safety, and performance</collab><source>Journal of Occupational and Environmental Medicine</source><year>2011</year><volume>53</volume><fpage>S1</fpage><lpage>S10</lpage></element-citation></ref><ref id="R42"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Slaven</surname><given-names>JE</given-names></name><name><surname>Mnatsakanova</surname><given-names>A</given-names></name><name><surname>Burchfiel</surname><given-names>CM</given-names></name><name><surname>Charles</surname><given-names>LE</given-names></name><name><surname>Smith</surname><given-names>LM</given-names></name><name><surname>Andrew</surname><given-names>ME</given-names></name><etal/></person-group><article-title>Association of sleep quality with depression in police officers</article-title><source>International Journal of Emergency Mental Health</source><year>2012</year><volume>13</volume><issue>4</issue><fpage>267</fpage><lpage>278</lpage><pub-id pub-id-type="pmid">22900460</pub-id></element-citation></ref><ref id="R43"><element-citation publication-type="gov"><collab>U.S. Bureau of Labor Statistics</collab><source>Employed and unemployed full- and part-time workers by age, sex, race, and Hispanic or Latino ethnicity, 2010</source><year>2011</year><comment>Retrieved from <ext-link ext-link-type="uri" xlink:href="http://www.bls.gov/cps/cpsaat8.pdf">http://www.bls.gov/cps/cpsaat8.pdf</ext-link></comment></element-citation></ref><ref id="R44"><element-citation publication-type="gov"><collab>U.S. Census Bureau</collab><source>Current Population Survey Design and Methodology. (U.S. Census Bureau, Technical Paper 66)</source><year>2006</year><comment>Retrieved from <ext-link ext-link-type="uri" xlink:href="http://www.census.gov/prod/2006pubs/tp-66.pdf">http://www.census.gov/prod/2006pubs/tp-66.pdf</ext-link></comment></element-citation></ref><ref id="R45"><element-citation publication-type="journal"><collab>U.S. Centers for Disease Control and Prevention</collab><source>Mental illness surveillance among adults in the United States (Morbidity and Mortality Weekly Report, 60(Suppl), 1&#x02013;29)</source><year>2011</year><comment>Retrieved from <ext-link ext-link-type="uri" xlink:href="http://www.cdc.gov/mmwr/pdf/other/su6003.pdf">http://www.cdc.gov/mmwr/pdf/other/su6003.pdf</ext-link></comment></element-citation></ref><ref id="R46"><element-citation publication-type="book"><collab>U.S. Department of Health and Human Services</collab><source>Healthy People 2010: understanding and improving health and objectives for improving health</source><year>2000</year><publisher-loc>Washington, DC</publisher-loc><publisher-name>Government Printing Office</publisher-name><comment>Retrieved from <ext-link ext-link-type="uri" xlink:href="http://www.cdc.gov/nchs/hphome.htm">http://www.cdc.gov/nchs/hphome.htm</ext-link></comment></element-citation></ref><ref id="R47"><element-citation publication-type="book"><collab>U.S. Department of Health and Human Services</collab><source>Mental Health: A report of the Surgeon General &#x02013; Executive Summary</source><year>1999</year><publisher-loc>Rockville, MD</publisher-loc><publisher-name>U.S. Department of Health and Human Services, Substance Abuse and Mental Health Services Administration, Center for Mental Health Services, National Institutes of Health, National Institute of Mental Health</publisher-name></element-citation></ref><ref id="R48"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Vena</surname><given-names>JE</given-names></name><name><surname>Violanti</surname><given-names>JM</given-names></name><name><surname>Marshall</surname><given-names>J</given-names></name><name><surname>Riedler</surname><given-names>RC</given-names></name></person-group><article-title>Mortality of a municipal worker cohort: III. Police officers</article-title><source>American Journal of Industrial Medicine</source><year>1986</year><volume>10</volume><fpage>383</fpage><lpage>397</lpage><pub-id pub-id-type="pmid">3788983</pub-id></element-citation></ref><ref id="R49"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Wang</surname><given-names>Y</given-names></name><name><surname>Beydoun</surname><given-names>MA</given-names></name></person-group><article-title>The obesity epidemic in the United States - Gender, age, socioeconomic, racial/ethnic, and geographic characteristics: A systematic review and meta-regression analysis</article-title><source>Epidemiology Reviews</source><year>2007</year><volume>29</volume><fpage>6</fpage><lpage>28</lpage></element-citation></ref><ref id="R50"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Wright</surname><given-names>BR</given-names></name><name><surname>Barbosa-Leiker</surname><given-names>C</given-names></name><name><surname>Hoekstra</surname><given-names>T</given-names></name></person-group><article-title>Law enforcement officer versus non-law enforcement officer status as a longitudinal predictor of traditional and emerging cardiovascular risk factors</article-title><source>Journal of Occupational and Environmental Medicine</source><year>2011</year><volume>53</volume><fpage>730</fpage><lpage>734</lpage><pub-id pub-id-type="pmid">21697738</pub-id></element-citation></ref></ref-list></back><floats-group><table-wrap id="T1" position="float" orientation="portrait"><label>Table 1</label><caption><p id="P32">Origin of general population estimates for key comparison characteristics</p></caption><table frame="box" rules="groups"><thead><tr><th align="left" rowspan="1" colspan="1">Variable</th><th align="left" rowspan="1" colspan="1">Reference Study</th><th align="left" rowspan="1" colspan="1">Study Population</th></tr></thead><tbody><tr><td align="left" rowspan="1" colspan="1"><bold>Demographics and Workplace</bold></td><td align="left" rowspan="1" colspan="1"/><td align="left" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Sex</td><td align="left" valign="top" rowspan="1" colspan="1"><xref rid="R43" ref-type="bibr">U.S. Current Population Survey (CPS), 2010</xref></td><td align="left" valign="top" rowspan="1" colspan="1">Full-time employed<break/>persons age &#x02265;20</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Race/Ethnicity</td><td align="left" valign="top" rowspan="1" colspan="1"><xref rid="R43" ref-type="bibr">U.S. CPS, 2010</xref></td><td align="left" valign="top" rowspan="1" colspan="1">Full-time employed<break/>persons age &#x02265;20</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Shift Work</td><td align="left" valign="top" rowspan="1" colspan="1">U.S. CPS Supplement, 2004</td><td align="left" valign="top" rowspan="1" colspan="1">All employed<break/>persons age &#x02265;20</td></tr><tr><td colspan="3" align="center" valign="bottom" rowspan="1"><hr/></td></tr><tr><td align="left" rowspan="1" colspan="1"><bold>Psychosocial Measures</bold></td><td align="left" rowspan="1" colspan="1"/><td align="left" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Depression</td><td align="left" valign="top" rowspan="1" colspan="1">National Health and Nutrition<break/>Examination Survey (NHANES),<break/>2005&#x02013;2008</td><td align="left" valign="top" rowspan="1" colspan="1">Adults age &#x02265;18</td></tr><tr><td colspan="3" align="center" valign="bottom" rowspan="1"><hr/></td></tr><tr><td align="left" rowspan="1" colspan="1"><bold>Lifestyle Behaviors</bold></td><td align="left" rowspan="1" colspan="1"/><td align="left" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Smoking Status</td><td align="left" valign="top" rowspan="1" colspan="1">Multi-Ethnic Study of Atherosclerosis<break/>(MESA), 2000&#x02013;2002</td><td align="left" valign="top" rowspan="1" colspan="1">2,801 employed<break/>adults age 45&#x02013;84</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Hours of Sleep</td><td align="left" valign="top" rowspan="1" colspan="1">National Health Interview<break/>Survey, 2004&#x02013;2007</td><td align="left" valign="top" rowspan="1" colspan="1">66,099 employed<break/>adults age &#x02265;18</td></tr><tr><td colspan="3" align="center" valign="bottom" rowspan="1"><hr/></td></tr><tr><td align="left" rowspan="1" colspan="1"><bold>Cardio-Metabolic Risk Factors</bold></td><td align="left" rowspan="1" colspan="1"/><td align="left" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Body Mass Index</td><td align="left" valign="top" rowspan="1" colspan="1">MESA, 2000&#x02013;2002</td><td align="left" valign="top" rowspan="1" colspan="1">2,801 employed<break/>adults age 45&#x02013;84</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Serum Cholesterol Levels</td><td align="left" valign="top" rowspan="1" colspan="1">MESA, 2000&#x02013;2002</td><td align="left" valign="top" rowspan="1" colspan="1">2,801 employed<break/>adults age 45&#x02013;84</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Hypertension</td><td align="left" valign="top" rowspan="1" colspan="1">MESA, 2000&#x02013;2002</td><td align="left" valign="top" rowspan="1" colspan="1">2,801 employed<break/>adults age 45&#x02013;84</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Glucose Intolerance</td><td align="left" valign="top" rowspan="1" colspan="1">NHANES, 2003&#x02013;2006</td><td align="left" valign="top" rowspan="1" colspan="1">3,423 adults age<break/>&#x02265;20</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Metabolic Syndrome</td><td align="left" valign="top" rowspan="1" colspan="1">NHANES, 1999&#x02013;2004</td><td align="left" valign="top" rowspan="1" colspan="1">8,457 employed<break/>adults age &#x02265;20</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Caritud Untima Media Thickness</td><td align="left" valign="top" rowspan="1" colspan="1">MESA, 2000&#x02013;2002</td><td align="left" valign="top" rowspan="1" colspan="1">2801 employed<break/>adults age 45&#x02013;84</td></tr></tbody></table></table-wrap><table-wrap id="T2" position="float" orientation="landscape"><label>Table 2</label><caption><p id="P33">Health disparities between BCOPS Study participants compared to the general U.S. employed population estimates.<xref ref-type="table-fn" rid="TFN13">*</xref></p></caption><table frame="box" rules="groups"><thead><tr><th rowspan="3" align="left" valign="middle" colspan="1">Variable</th><th colspan="3" align="center" valign="middle" rowspan="1">BCOPS</th><th colspan="3" align="center" valign="middle" rowspan="1">General Employed<break/>Population Estimate</th></tr><tr><th colspan="6" align="center" valign="bottom" rowspan="1"><hr/></th></tr><tr><th align="right" valign="bottom" rowspan="1" colspan="1">N or %</th><th align="center" valign="bottom" rowspan="1" colspan="1">Mean<break/>Age</th><th align="center" valign="bottom" rowspan="1" colspan="1">%<break/>Women</th><th align="right" valign="bottom" rowspan="1" colspan="1">N or %</th><th align="center" valign="bottom" rowspan="1" colspan="1">Mean<break/>Age</th><th align="center" valign="bottom" rowspan="1" colspan="1">%<break/>Women</th></tr></thead><tbody><tr><td align="left" valign="top" rowspan="1" colspan="1"><bold>Demographics and Workplace</bold><break/><bold>Characteristics</bold></td><td align="right" rowspan="1" colspan="1"/><td align="center" rowspan="1" colspan="1"/><td align="center" rowspan="1" colspan="1"/><td align="right" rowspan="1" colspan="1"/><td align="center" rowspan="1" colspan="1"/><td align="center" rowspan="1" colspan="1"/></tr><tr><td align="left" rowspan="1" colspan="1">Men, %</td><td align="right" rowspan="1" colspan="1">73.8<xref ref-type="table-fn" rid="TFN2">a</xref></td><td align="center" rowspan="1" colspan="1">41.5</td><td align="center" rowspan="1" colspan="1">-</td><td align="right" rowspan="1" colspan="1">57.6<xref ref-type="table-fn" rid="TFN3">b</xref></td><td align="center" rowspan="1" colspan="1">43.1</td><td align="center" rowspan="1" colspan="1">-</td></tr><tr><td align="left" rowspan="1" colspan="1">Women, %</td><td align="right" rowspan="1" colspan="1">26.2<xref ref-type="table-fn" rid="TFN2">a</xref></td><td align="center" rowspan="1" colspan="1">41.5</td><td align="center" rowspan="1" colspan="1">-</td><td align="right" rowspan="1" colspan="1">42.4<xref ref-type="table-fn" rid="TFN3">b</xref></td><td align="center" rowspan="1" colspan="1">43.1</td><td align="center" rowspan="1" colspan="1">-</td></tr><tr><td align="left" rowspan="1" colspan="1">White, %</td><td align="right" rowspan="1" colspan="1">76.7<xref ref-type="table-fn" rid="TFN2">a</xref></td><td align="center" rowspan="1" colspan="1">41.5</td><td align="center" rowspan="1" colspan="1">26.2</td><td align="right" rowspan="1" colspan="1">81.4<xref ref-type="table-fn" rid="TFN3">b</xref></td><td align="center" rowspan="1" colspan="1">43.1</td><td align="center" rowspan="1" colspan="1">42.4</td></tr><tr><td align="left" rowspan="1" colspan="1">Black, %</td><td align="right" rowspan="1" colspan="1">20.3<xref ref-type="table-fn" rid="TFN2">a</xref></td><td align="center" rowspan="1" colspan="1">41.5</td><td align="center" rowspan="1" colspan="1">26.2</td><td align="right" rowspan="1" colspan="1">11.2<xref ref-type="table-fn" rid="TFN3">b</xref></td><td align="center" rowspan="1" colspan="1">43.1</td><td align="center" rowspan="1" colspan="1">42.4</td></tr><tr><td align="left" rowspan="1" colspan="1">Hispanic<xref ref-type="table-fn" rid="TFN14">**</xref>, %</td><td align="right" rowspan="1" colspan="1">1.8<xref ref-type="table-fn" rid="TFN2">a</xref></td><td align="center" rowspan="1" colspan="1">41.5</td><td align="center" rowspan="1" colspan="1">26.2</td><td align="right" rowspan="1" colspan="1">14.3<xref ref-type="table-fn" rid="TFN3">b</xref></td><td align="center" rowspan="1" colspan="1">43.1</td><td align="center" rowspan="1" colspan="1">42.4</td></tr><tr><td align="left" rowspan="1" colspan="1">Day Shift, %</td><td align="right" rowspan="1" colspan="1">53.1<xref ref-type="table-fn" rid="TFN4">c</xref></td><td align="center" rowspan="1" colspan="1">41.2</td><td align="center" rowspan="1" colspan="1">28.6</td><td align="right" rowspan="1" colspan="1">84.0<xref ref-type="table-fn" rid="TFN5">d</xref></td><td align="center" rowspan="1" colspan="1">40.5</td><td align="center" rowspan="1" colspan="1">48.2</td></tr><tr><td align="left" rowspan="1" colspan="1">Afternoon Shift, %</td><td align="right" rowspan="1" colspan="1">26.3<xref ref-type="table-fn" rid="TFN4">c</xref></td><td align="center" rowspan="1" colspan="1">41.2</td><td align="center" rowspan="1" colspan="1">28.6</td><td align="right" rowspan="1" colspan="1">3.1<xref ref-type="table-fn" rid="TFN5">d</xref></td><td align="center" rowspan="1" colspan="1">40.5</td><td align="center" rowspan="1" colspan="1">48.2</td></tr><tr><td align="left" rowspan="1" colspan="1">Night Shift, %</td><td align="right" rowspan="1" colspan="1">20.6<xref ref-type="table-fn" rid="TFN4">c</xref></td><td align="center" rowspan="1" colspan="1">41.2</td><td align="center" rowspan="1" colspan="1">28.6</td><td align="right" rowspan="1" colspan="1">5.6<xref ref-type="table-fn" rid="TFN5">d</xref></td><td align="center" rowspan="1" colspan="1">40.5</td><td align="center" rowspan="1" colspan="1">48.2</td></tr><tr><td align="left" rowspan="1" colspan="1"><bold>Psychosocial Measures</bold></td><td align="right" rowspan="1" colspan="1"/><td align="center" rowspan="1" colspan="1"/><td align="center" rowspan="1" colspan="1"/><td align="right" rowspan="1" colspan="1"/><td align="center" rowspan="1" colspan="1"/><td align="center" rowspan="1" colspan="1"/></tr><tr><td align="left" rowspan="1" colspan="1">Depression, %</td><td align="right" rowspan="1" colspan="1">12.0<xref ref-type="table-fn" rid="TFN6">e</xref></td><td align="center" rowspan="1" colspan="1">40.7</td><td align="center" rowspan="1" colspan="1">27.4</td><td align="right" rowspan="1" colspan="1">6.8<xref ref-type="table-fn" rid="TFN7">f</xref></td><td align="center" rowspan="1" colspan="1">48.3</td><td align="center" rowspan="1" colspan="1">50.6</td></tr><tr><td align="left" rowspan="1" colspan="1"><bold>Lifestyle Behaviors</bold></td><td align="right" rowspan="1" colspan="1"/><td align="center" rowspan="1" colspan="1"/><td align="center" rowspan="1" colspan="1"/><td align="right" rowspan="1" colspan="1"/><td align="center" rowspan="1" colspan="1"/><td align="center" rowspan="1" colspan="1"/></tr><tr><td align="left" rowspan="1" colspan="1">Current Smokers, %</td><td align="right" rowspan="1" colspan="1">16.7<xref ref-type="table-fn" rid="TFN2">a</xref></td><td align="center" rowspan="1" colspan="1">41.5</td><td align="center" rowspan="1" colspan="1">26.2</td><td align="right" rowspan="1" colspan="1">13.6<xref ref-type="table-fn" rid="TFN8">g</xref></td><td align="center" rowspan="1" colspan="1">56.4</td><td align="center" rowspan="1" colspan="1">46.9</td></tr><tr><td align="left" rowspan="1" colspan="1">Sleep &#x0003c; 6 hours/24 hour period, %</td><td align="right" rowspan="1" colspan="1">33.0<xref ref-type="table-fn" rid="TFN6">e</xref></td><td align="center" rowspan="1" colspan="1">40.7</td><td align="center" rowspan="1" colspan="1">27.4</td><td align="right" rowspan="1" colspan="1">8.0<xref ref-type="table-fn" rid="TFN9">h</xref></td><td align="center" rowspan="1" colspan="1">41.5</td><td align="center" rowspan="1" colspan="1">50.1</td></tr><tr><td align="left" rowspan="1" colspan="1"><bold>Cardio-metabolic Risk Factors</bold></td><td align="right" rowspan="1" colspan="1"/><td align="center" rowspan="1" colspan="1"/><td align="center" rowspan="1" colspan="1"/><td align="right" rowspan="1" colspan="1"/><td align="center" rowspan="1" colspan="1"/><td align="center" rowspan="1" colspan="1"/></tr><tr><td align="left" rowspan="1" colspan="1">Overweight (BMI 25&#x02013;29.9 kg/m&#x000b2;), %</td><td align="right" rowspan="1" colspan="1">41.5<xref ref-type="table-fn" rid="TFN2">a</xref></td><td align="center" rowspan="1" colspan="1">41.5</td><td align="center" rowspan="1" colspan="1">26.2</td><td align="right" rowspan="1" colspan="1">40.0<xref ref-type="table-fn" rid="TFN8">g</xref></td><td align="center" rowspan="1" colspan="1">56.4</td><td align="center" rowspan="1" colspan="1">46.9</td></tr><tr><td align="left" rowspan="1" colspan="1">Obese (BMI &#x02265; 30 kg/m&#x000b2;), %</td><td align="right" rowspan="1" colspan="1">40.5<xref ref-type="table-fn" rid="TFN2">a</xref></td><td align="center" rowspan="1" colspan="1">41.5</td><td align="center" rowspan="1" colspan="1">26.2</td><td align="right" rowspan="1" colspan="1">32.1<xref ref-type="table-fn" rid="TFN8">g</xref></td><td align="center" rowspan="1" colspan="1">56.4</td><td align="center" rowspan="1" colspan="1">46.9</td></tr><tr><td align="left" rowspan="1" colspan="1">Total Cholesterol, mg/dL</td><td align="right" rowspan="1" colspan="1">200.8<xref ref-type="table-fn" rid="TFN10">i</xref></td><td align="center" rowspan="1" colspan="1">41.1</td><td align="center" rowspan="1" colspan="1">25.9</td><td align="right" rowspan="1" colspan="1">193.2<xref ref-type="table-fn" rid="TFN8">g</xref></td><td align="center" rowspan="1" colspan="1">56.4</td><td align="center" rowspan="1" colspan="1">46.9</td></tr><tr><td align="left" rowspan="1" colspan="1">Systolic Blood Pressure, mm Hg</td><td align="right" rowspan="1" colspan="1">120.9<xref ref-type="table-fn" rid="TFN10">i</xref></td><td align="center" rowspan="1" colspan="1">41.1</td><td align="center" rowspan="1" colspan="1">25.9</td><td align="right" rowspan="1" colspan="1">121.6<xref ref-type="table-fn" rid="TFN8">g</xref></td><td align="center" rowspan="1" colspan="1">56.4</td><td align="center" rowspan="1" colspan="1">46.9</td></tr><tr><td align="left" rowspan="1" colspan="1">Glucose Intolerance, %</td><td align="right" rowspan="1" colspan="1">23.6<xref ref-type="table-fn" rid="TFN2">a</xref></td><td align="center" rowspan="1" colspan="1">41.5</td><td align="center" rowspan="1" colspan="1">26.2</td><td align="right" rowspan="1" colspan="1">32.4<xref ref-type="table-fn" rid="TFN11">j</xref></td><td align="center" rowspan="1" colspan="1">39.5</td><td align="center" rowspan="1" colspan="1">47.6</td></tr><tr><td align="left" rowspan="1" colspan="1">Metabolic Syndrome, %</td><td align="right" rowspan="1" colspan="1">26.7<xref ref-type="table-fn" rid="TFN2">a</xref></td><td align="center" rowspan="1" colspan="1">41.5</td><td align="center" rowspan="1" colspan="1">26.2</td><td align="right" rowspan="1" colspan="1">18.7<xref ref-type="table-fn" rid="TFN12">k</xref></td><td align="center" rowspan="1" colspan="1">41.0</td><td align="center" rowspan="1" colspan="1">46.5</td></tr><tr><td align="left" rowspan="1" colspan="1">Carotid Intima Media Thickness, mm</td><td align="right" rowspan="1" colspan="1">0.62<xref ref-type="table-fn" rid="TFN10">i</xref></td><td align="center" rowspan="1" colspan="1">41.1</td><td align="center" rowspan="1" colspan="1">25.9</td><td align="right" rowspan="1" colspan="1">0.82<xref ref-type="table-fn" rid="TFN8">g</xref></td><td align="center" rowspan="1" colspan="1">56.4</td><td align="center" rowspan="1" colspan="1">46.9</td></tr></tbody></table><table-wrap-foot><fn id="TFN1"><p id="P34">Data Sources.</p></fn><fn id="TFN2"><label>a:</label><p id="P35"><xref rid="R19" ref-type="bibr">Hartley, 2012</xref>;</p></fn><fn id="TFN3"><label>b:</label><p id="P36">U.S. Bureau of Labor Statistics Household Data;</p></fn><fn id="TFN4"><label>c:</label><p id="P37"><xref rid="R24" ref-type="bibr">Ma, 2011</xref>;</p></fn><fn id="TFN5"><label>d:</label><p id="P38"><xref rid="R26" ref-type="bibr">McMenamin, 2007</xref>;</p></fn><fn id="TFN6"><label>e:</label><p id="P39"><xref rid="R42" ref-type="bibr">Slaven, 2012</xref>;</p></fn><fn id="TFN7"><label>f:</label><p id="P40"><xref rid="R45" ref-type="bibr">MMWR, 2011</xref>;</p></fn><fn id="TFN8"><label>g:</label><p id="P41"><xref rid="R14" ref-type="bibr">Fujishiro, 2011</xref>;</p></fn><fn id="TFN9"><label>h:</label><p id="P42"><xref rid="R23" ref-type="bibr">Luckhaupt, 2010</xref>;</p></fn><fn id="TFN10"><label>i:</label><p id="P43"><xref rid="R18" ref-type="bibr">Hartley, 2011</xref>;</p></fn><fn id="TFN11"><label>j:</label><p id="P44"><xref rid="R11" ref-type="bibr">Ervin, 2009</xref>;</p></fn><fn id="TFN12"><label>k:</label><p id="P45"><xref rid="R9" ref-type="bibr">Davila, 2010</xref></p></fn><fn id="TFN13"><label>*</label><p id="P46">The study populations for depression and glucose intolerance were not restricted by employed status.</p></fn><fn id="TFN14"><label>**</label><p id="P47">Hispanic race or ethnicity. In BCOPS, Hispanic was collected as &#x0201c;Race&#x0201d;. In BLS, Hispanic was collected as &#x0201c;Ethnicity&#x0201d;. A person could then list &#x0201c;Race&#x0201d; as &#x0201c;White&#x0201d; and also list &#x0201c;Ethnicity&#x0201d; as &#x0201c;Hispanic&#x0201d;. As a result, the BLS percentages will not sum to 100 like those for BCOPS.</p></fn></table-wrap-foot></table-wrap></floats-group></article>