In the general population, cardiovascular disease (CVD) is the leading cause of death and disability, accounting for a large percentage of overall health care burden (www.cdc.gov/heartdisease/facts.htm). Among Veterans, there may be even greater risk for CVD including ischemic heart disease,1,2 in part because of the added risk that accompanies lifestyle features of military service, combat,3 occupational exposures, and comorbid mental health conditions such as posttraumatic stress disorder (PTSD)4,5 which is up to 5 times more prevalent among Veterans than non-Veterans (www.ptsd.va.gov/professional/PTSD-overview/epidemiological-facts-ptsd.asp).
While on active duty, men and women service members must maintain weight and fitness standards6 ostensibly contributing to relatively low rates of obesity and related cardiovascular (CV) risk factors such as hypertension and diabetes, but after leaving military service, they may develop incident CV risk factors at similar or greater rates than the general population. Mental health sequelae of military service have previously been shown to contribute to development of CV risk factors such as hypertension7 and to health risk behaviors such as smoking. Demographic factors, such as sex, are associated with obesity trajectories in returning Veterans.8 In addition, stressors of transition to civilian life may further differ by sex and contribute to behaviors that impact CV risk.9
Although it is traditionally thought that women are at relatively lower risk for incident CVD than men, diseases of the heart are in fact the leading cause of death among women as well,10,11 particularly as they age. In studies of CV risk factors among Veterans, women have poorer control of hypertension, diabetes, and hyperlipidemia than men.12–14 In addition, women Veterans have higher rates of certain mental health conditions, including depression15 than men. Unique stressors associated with reintegration for women16–18 may impact psychological well-being and behaviors that result in increased incidence rates for CV risk factors and disease.
In addition to sex, race may impact rates of CV risk factors with hypertension, diabetes, and obesity occurring at higher rates in racial and ethnic minority populations.19–21 In a recent study among Veteran patients, black/African American Veterans had higher blood pressure (BP), low-density lipoprotein (LDL) cholesterol, and hemoglobin A1c (HbA1C) levels than whites after adjusting for age.12
Knowledge of incidence rates for CV risk factors after leaving military service and how these may vary by demographic status will be crucial for the Department of Defense and the Department of Veterans Affairs as they determine how to tailor interventions to prevent accelerated development of CV risk factors in the military population.
We hypothesize that after returning from deployment and enrolling for Veterans Affairs (VA) care, both men and women Veterans using Veterans Health Administration (VHA) would rapidly develop CV risk factors such as hypertension, hyperlipidemia, obesity, and diabetes, at rates higher than the general population. In addition, we expected the differential development of these factors in women and men would be moderated by race and mental health conditions (PTSD and depression). Using electronic health record (EHR) data from the VHA, we sought to measure the sex-specific incidence of newly diagnosed CV risk factors and disease in Veterans returning from service to Operations Iraqi Freedom, Enduring Freedom, and New Dawn (OEF/OIF/OND) from 2001 to 2014 and determine whether differences by sex were modified by race and mental health conditions.
Data Sources and Study Population
The study sample was comprised Veterans from the roster maintained by the Defense Manpower Data Center–Contingency Tracking System Deployment File. Individuals who served in support of OIF/OEF/OND and enrolled with the VHA are included. The roster includes their demographics and deployment history. For the analyses, we included Veterans: (1) whose end of last deployment was between October 1, 2001 and July 31, 2014; and (2) whose first VA medical visit was between October 1, 2001 and October 7, 2014. In addition to the demographic and deployment history data included in the roster, EHR data were extracted from the Corporate Data Warehouse that includes the VHA’s extensive EHR, with information on health care utilization, pharmacy, laboratory, vital signs, coded diagnostic, and procedural data [International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) and current procedural terminology] associated with all VA inpatient and outpatient encounters. Corporate Data Warehouse data were available from 2001 to 2014. Participant follow-up was accrued until their last patient visit that occurred before or on October 1, 2015.
To capture newly diagnosed risk factors, we excluded Veterans with a prevalent ICD-9-CM diagnosis of hypertension, obesity, dyslipidemia, diabetes, or coronary artery disease (CAD) or with measured BP [systolic blood pressure (SBP)>140, diastolic blood pressure (DBP)>90 mm Hg], body mass index (BMI)>30 kg/m2, LDL>160 mg/dL, high-density lipoprotein (HDL)<40 mg/dL, triglycerides (TG)>150 mg/dL, or HbA1C>6.5% during a baseline period encompassing the date of first primary care (PC) visit plus 180 days. The 180-day period was chosen to maximize the likelihood of identifying prevalent risk factors in the EHR. Veterans without a measured BMI or BP during this baseline period were excluded. The final cohort free of CV risk factors at baseline included 267,305 Veterans.
Definition of Incident Risk Factors
Incident risk factors (hypertension, obesity, dyslipidemia, diabetes) were identified through new ICD-9-CM diagnostic codes (Appendix 1, Supplemental Digital Content 1, http://links.lww.com/MLR/B474) or measurement recordings at any PC visit following the baseline period. For all variables using ICD-9-CM diagnostic codes, Veterans were only considered to have a diagnosis if codes occurred on ≥2 outpatient visits (on separate days), or ≥1 inpatient visit. This methodology has been used for the identification of psychiatric disorders in administrative data22 and Human Immunodeficiency Virus in Medicaid data.23 Diagnostic code groupings were previously validated.24
Incident hypertension was defined as a new diagnosis of hypertension in the EHR or 2 hypertensive BP recordings (SBP>140, DBP>90 mm Hg) on 2 separate days in the EHR. Obesity was defined as a BMI>30 kg/m2, and dyslipidemia as either a laboratory elevation in lipids (LDL>160 or TG>150 or HDL<40 mg/dL), a new prescription for a cholesterol-lowering agent (lovastatin, atorvastatin, fluvastatin, simvastatin, pitavastatin, rosuvastatin, pravastatin) or a diagnosis of dyslipidemia. Diabetes was determined by either a new diagnosis of diabetes or a laboratory HbA1c>6.5%. Incident CAD was identified via diagnostic codes. The incidence of new smoking postdeployment was not investigated as a CV risk factor given the already high uptake of smoking in the military.25 Women with pregnancies were excluded from the dataset due to confounding effects on the BMI.
Age, race, education, marital status, number of deployments, and branch of military service were obtained from the roster. Smoking status was identified by health factors ascertained through the national smoking clinical reminder system, in which Veterans are queried about smoking status at PC appointments.26 Baseline prevalence of PTSD (ICD-9-CM 309.81), major or mild depression, alcohol use disorder, and substance use disorder were assessed via ICD-9 codes.
Person-time was defined as the time in years from the end of the baseline period (first PC visit+180 days) until either an event occurred or the last recorded visit before October 1, 2015 (censoring). Incidence rates for each event were estimated by dividing the total number of events by the total person-years (py) follow-up and multiplying by 1000 (ie, events per 1000 py).
Cumulative incidence was estimated using the Kaplan Meier method. Adjusted hazard ratios (HRs) were estimated using Cox regression. Covariates included age, race, education, branch of service, alcohol use disorder, substance use disorder, mild depression, major depression, PTSD, smoking status, multiple deployment (yes/no), and time since last deployment. Interactions of sex with race, PTSD, and depression were evaluated to determine whether these factors modified the impact of sex on the development of risk factors. For these analyses depression was defined as either major or mild depression to assure a large enough prevalence. Piecewise exponential models were used to determine whether the relations of sex with risk factors varied across follow-up time (ie, did HRs change across follow-up time). The piecewise exponential model permits the evaluation of changes in hazards over time by breaking up follow-up time into intervals and assuming the hazard is constant within each interval but allowed to vary across intervals.27
Of the 1,063,813 OEF/OIF/OND Veterans on the roster, 573,862 had >180 days of follow-up and a measured baseline BP and BMI. Of these, 267,305 (47%) did not have a risk factor during the baseline period. Those with a risk factor prevalent during the baseline period (n=306,557) were older, more likely to be male, nonwhite, married, depressed, and have PTSD compared with those without a risk factor (Table 1).
In those without a prevalent baseline risk factor there were significant demographic differences by sex. Women Veterans were more likely than men to be black/African American (25% vs. 12%), not married (66% vs. 56%), higher educated (24% vs. 17%), and have major or mild depression (15% vs. 11%). Women were less likely to smoke (26% vs. 43%), use alcohol (2% vs. 4%), have PTSD (11% vs. 15%) or have multiple deployments (40% vs. 48%). The average time since last deployment to enrollment in VA care was 2.4 years.
Incidence of CV Risk Factors and CAD in Women and Men
The rate of developing at least 1 risk factor or CAD was 240 and 151 per 1000 py in men and women, respectively (Table 2). The highest overall rate was for dyslipidemia (150 and 75 per 1000 py in men and women, respectively). Except for obesity, women were significantly less likely to develop any other factor (crude HRs ranging from 0.44 to 0.82). Adjusted HRs remained significant. In addition, after adjustment, women were significantly more likely to become obese (adjusted HR=1.05, 95% confidence interval=1.02–1.07). Cumulative incidence plots demonstrate the high likelihood of developing at least 1 CV risk factor (Fig. 1A), with 68% of men and 50% of women developing a risk factor within 5 years.
Effect Modification of the Relation of Sex and CV Risk Factor Development by Race
For the combined event (any risk factor) and hypertension, the protective effect of female sex was of smaller magnitude in blacks/African Americans compared with other races (sex by race interactions, P<0.001) (Table 3). The increased risk of obesity in women compared with men was magnified for blacks/African Americans compared with whites or Hispanics (P<0.001). HRs for dyslipidemia, diabetes, and CAD were not significantly altered by race.
Effect Modification of the Relation of Sex and CV Risk Factor Development by PTSD and Depression
A diagnosis of PTSD at baseline did not significantly modify the relation of sex with the development of any risk factor (Table 4) as HRs comparing women with men were similar in those with and without PTSD. Depression (defined as either major or mild) moderated the impact of sex on the development of any risk factor (P=0.007) as the protective effect of being a women was slightly greater in those who were not depressed (HR=0.63) compared with those who were depressed (HR=0.67). This observation was not common across all risk factors and was primarily driven by the development of obesity. The increased risk of obesity observed in women was magnified in those who were depressed (HR=1.17) compared with those who were not depressed (HR=1.01, P<0.001).
Changes in the Relation of Sex With Risk Factor Development During Follow-up
With the exception of hypertension, the relation between sex and risk factors did not significantly vary over time (data not shown). HRs for sex increased over time for hypertension (HR years 0–2=0.59, HR years 2–4=0.63, HR years 4–6=0.66, HR years 6+=0.72; sex by time interaction, P<0.001) indicating that the protective effect of female sex declined over time.
Several factors associated with military service, including combat exposure, the high incidence of mental health conditions, and tobacco use, that accompany this service may increase incident CVD risk and the development of CV risk factors. In addition, when Veterans enter VHA care and no longer have the structure of military service—with its associated weight restrictions and physical training requirements, risk for incident CV risk factors may increase. Because of sex differences in mental health conditions and stressors associated with transition from active duty to Veteran status, it is important to examine sex differences in the incidence of these risk factors. In this study, we assessed prevalent CV risk factors at entry into VHA, the incidence of newly diagnosed CV risk factors by sex, and how this effect is modified by race and mental health conditions, in a cohort of young Veterans (mean age, 28 y) who served during OEF/OIF/OND and subsequently registered with and used the VHA (on an average 2.4 y since last deployment). Interestingly, although Veterans are held to weight and fitness standards, we found over 50% had a CV risk factor at entry into VHA care. For those without CV risk at entry, we found high incidence rates of CV risk factors over time for both men and women Veterans. The annual incidence rate for any CV risk factor was 240 per 1000 py in men and 150 per 1000 py in women. Furthermore, 68% of men and 50% of women developed at least 1 CV risk factor after 5 years, and 86% of men and 70% of women developed a CV risk factor by 10 years. Women Veterans were more likely to become obese, but less likely to develop any other risk factor overall.
Although comparisons to the general population are hindered by age, race, and sex differences, varying periods of follow-up, and date of study, Veterans entering VHA care appear to have strikingly higher incidence rates for hypertension compared with civilian populations.28–30 In the Cardiovascular Risk Development in Young Adults (CARDIA) study the 10-year incidence of hypertension in young adults who were 18–30 years old at the start of the study, was 16.4% in men and 13.1% in women for blacks, and 7.8% in men and 3.2% in women for whites.28 In comparison, OEF/OIF/OND Veterans in the current cohort had higher annual incidence rates of 69 and 41 per 1000 py, translating into 10-year cumulative incidences of 42% and 28% for men and women, respectively.
Similarly, we observed higher incidence rates of obesity in this Veteran population compared with other studies of the general population. The Behavioral Risk Factor Surveillance Study among US adults above 18 years of age31 showed a similar age adjusted annual incidence of obesity of 5.4% for women but a lower rate of 3.2% for men. The Framingham study32 showed a yearly incidence rate of 2% in men and 1.9% in women. Our findings [yearly incidence rates of 5.8% for women and 5.7% for men (Table 2)] are consistent with other studies that have reported high rates of obesity among Veterans.33–35
In contrast to hypertension and obesity, incidence rates for diabetes appear to be similar, but slightly lower for Veteran than non-Veteran cohorts. Recent CDC data (www.cdc.gov/diabetes/data/national.html) shows higher rates for women compared with men (2.8/1000 py for men age 18–44 and 3.5/1000 py for women), compared with 2.0 for men and 1.7 for women in our study.
Although, we found overall high incidence rates of hypertension and obesity among Veterans in VHA care, we found lower incidence rates and lower unadjusted and adjusted HRs for hypertension, dyslipidemia, and diabetes for women compared with men. This may due to the young age of the cohort and attributable in part to the lower risk for CV risk factors and events in women before menopause. Nevertheless, our results are mostly consistent with those of Vimalananda et al36 and other studies15,37 that found higher prevalence rates of hypertension, hyperlipidemia, and diabetes among men than women Veterans but similar rates of obesity.
Among women and men Veterans studies have shown poorer health outcomes38 and increased CV risk among those with mental health conditions39–42 and women Veterans have higher rates of most mental health conditions15 yet little is known about whether these conditions may have a greater impact on the development of CV risk factors for women. We compared HRs for incidence of hypertension, obesity, dyslipidemia, diabetes, and CAD for men and women Veterans with and without PTSD and depression and found no modification of the impact of sex on risk of hypertension, diabetes, obesity, or CAD by PTSD. Depression modified the sex effect on the combined event (any risk factor) and of obesity so that the increased risk of obesity for women compared with men was magnified in those who were depressed. This effect on the combined event (any risk factor) was not consistent across the other risk factors and was primarily driven by obesity. We did not find that the sex difference in risk for CAD was modified by depression. This is in contrast with results of other studies that have found differential impacts of depression on CAD by sex.43,44 Our results indicate that PTSD and depression do not modify the impact of sex on CAD or CAD risk factors, except obesity, and may be equally salient risk factors for both men and women in the Veteran population.
Because CV risk varies by race19–21 we also assessed whether race modified the incidence of risk factors by sex. Our results showed that the protective effect of female sex was smaller for the combined outcome of any CV risk factor, and for hypertension in black/African American women, and that the hazard for obesity was greater in black/African American women. This is consistent with recent studies by Goldstein et al12 and Rose et al45 showing higher rates of hypertension, and obesity in black/African American compared with white women Veterans.
This study has several limitations. First, these findings cannot be generalized to all Veterans, as we only had access to data from Veterans who had enrolled in and used VA care. It is likely that incidence for CV risk factors in our study population is higher than the general population of OIF/OEF/OND Veteran’s as those that seek VHA health care may be less healthy. Our estimates of the prevalence of physical and mental health problems among these Veterans overall may also be biased, because certain health conditions may cause barriers to care, and others may make Veterans more likely to seek care. In particular, rates of CV risk factors may be high at entry into VA, because Veterans with service connected medical conditions may be more likely to enroll for VA care. Another important limitation is that because we relied on ICD-9-CM codes in EHR to capture physical and mental health conditions, some of our findings may be subject to misclassification bias. We cannot assume causality specifically related to trauma exposure because of limitations to our EHR data, and we cannot necessarily assume causality from military service. Our comparisons to non-Veteran population are hindered by differences noted above, including differences in the time period of study.
This study suggests the need for further examination of the impact of military service on CV risk factors and disease in Veterans who use and do not use the VHA. Department of Defense and VHA programs should target recently deployed service members and Veterans with strategies aimed at CV prevention, including lifestyle modifications, to lower CV risk with tailored programs for specifically vulnerable populations.
1. Page WF, Brass LM. Long-term heart disease and stroke mortality among former American prisoners of war of World War II and the Korean Conflict: results of a 50-year follow-up. Mil Med. 2001;166:803–808.
2. Page WF, Ostfeld AM. Malnutrition and subsequent ischemic heart disease in former prisoners of war of World War II and the Korean conflict. J Clin Epidemiol. 1994;47:1437–1441.
3. Crum-Cianflore NF, Bagtnell ME, Schaller E, et al. Impact of combat deployment and posttraumatic stress disorder on newly reported coronary heart disease among US active duty and reserve forces. Circulation. 2014;19:1813–1820.
4. Beristianos MH, Yaffe K, Cohen B, et al. PTSD and risk of incident cardiovascular disease in aging Veterans. Am J Geriatr Psychiatry. 2016;24:192–200.
5. Edmondson E, Kronish IM, Shaffer JA, et al. Posttraumatic stress disorder and risk for coronary heart disease: a meta-analytic review. Am Heart J. 2013;166:806–814.
6. Institute of Medicine (US) Subcommittee on Military Weight Management. Weight Management: State of the Science and Opportunities for Military Programs. Washington, DC: National Academies Press; 2004. 2, Military Standards for Fitness, Weight, and Body Composition.
7. Burg MM, Brandt C, Buta E, et al. Risk for incident hypertension associated with posttraumatic stress disorder in military Veterans, and the effect of PTSD treatment. Psychosomatic Med. 2017;79:181–188.
8. Rosenberger PH, Ning Y, Brandt C, et al. BMI trajectory groups in Veterans of the Iraq and Afghanistan Wars. Prev Med. 2011;53:249–254.
9. Mattocks KM, Haskell SG, Krebs EE, et al. Women at war: understanding how women veterans cope with combat and military sexual trauma. Soc Sci Med. 2012;74:537–545.
10. Murphy SL, Xu J, Kochanek KD. Deaths: final data for 2010. Natl Vital Stat Rep. 2013;61:1–117.
11. Go AS, Mozaffarian D, Roger VL, et al. On Behalf of the American Heart Association Statistics Committee and Stroke Statistics Subcommittee. Heart disease and stroke statistics—2013 update: a report from the American Heart Association. Circulation. 2013;127:e6–e245.
12. Goldstein KM, Meinyk SD, Zullig LL, et al. Heart matters: gender and racial differences in cardiovascular disease risk factor control among veterans. Womens Health Issues. 2014;24:477–483.
13. Vimalananda VG, Miller DR, Palnati M, et al. Gender disparities in lipid-lowering therapy among veterans with diabetes. Womens Health Issues. 2011;21(suppl):S176–S181.
14. Jackson GL, Edelman D, Weinberger M. Simultaneous control of intermediate diabetes outcomes among Veterans Affairs primary care patients. J Gen Intern Med. 2006;21:1050–1056.
15. Frayne SM, Phibbs CS, Saechao F, et al. Sourcebook: Women Veterans in the Veterans Health Administration Volume 3 Sociodemographics, Utilization, Costs of Care, and Health Profile Women’s Health
Evaluation Initiative, Women’s Health
Services, Veterans Health Administration. Washington, DC: Department of Veterans Affairs; 2014.
16. Smith BN, Wang JM, Vaughn-Coaxum RA, et al. Anxiety stress coping. The role of post-deployment social factors in linking deployment experiences and current posttraumatic stress disorder symptomatology among male and female Veterans anxiety stress coping. 2016;27:1–13.
17. Maiocco G, Smith MJ. The experience of women Veterans coming back from war. Arch Psychiatr Nurs. 2016;30:393–399.
18. Villagran M, Ledford CJ, Canzona MR. Women’s health
identities in the transition from military member to service Veteran. J Health Commun. 2015;20:1125–1132.
19. Howard G, Safford MM, Moy CS, et al. Racial differences in the incidence of cardiovascular risk
factors in older black and white adults. J Am Geriatr Soc. 2017;65:83–90.
20. Bhupathiraju SN, Hu FB. Epidemiology of obesity and diabetes and their cardiovascular complications. Circ Res. 2016;118:1723–1735.
21. Graham G. Disparities in cardiovascular disease risk in the United States. Curr Cardiol Rev. 2015;11:238–245. Review.
22. Lurie N, Popkin M, Dysken M, et al. Accuracy of diagnoses of schizophrenia in Medicaid claims. Hosp Community Psychiatry. 1992;43:69–71.
23. Walkup JT, Wei W, Sambamoorthi U, et al. Sensitivity of an AIDS case-finding algorithm: who are we missing? Med Care. 2004;42:756–763.
25. Nelson JP, Pederson LL, Lewis J. Tobacco use in the army: illuminating patterns, practices and options for treatment. Mil Med. 2009;174:162–169.
26. McGinnis KA, Brandt CA, Skanderson M, et al. Validating smoking data from the Veteran’s Affairs health factors dataset, an electronic data source. Nicotine Tob Res. 2011;13:1233–1239.
27. Friedman M. Piecewise exponential models for survival data with covariates. Ann Statist. 1982;10:101–113.
28. Kiefe CI, Williams OD, Bild DE, et al. Regional disparities in the incidence of elevated blood pressure among young adults: the CARDIA study. Circulation. 1997;96:1082–1088.
29. Lacruz ME, Kluttig A, Hartwig S, et al. Prevalence and incidence of hypertension in the general adult population. Results of the CARLA-cohort study. Medicine. 2015;94:1–7.
30. Tu K, Chen Z, Lipscombe LL. Prevalence and incidence of hypertension from 1995-2005; a population-based study. CMAJ. 2008;178:1429–1435.
31. Pan L, Freedman DS, Gillespie C, et al. Incidences of obesity and extreme obesity among US adults: findings from the 2009 Behavioral Risk Factor Surveillance System. Popul Health Metr. 2011;9:56.
32. Parikh NI, Pencina MJ, Wang TJ, et al. Increasing trends in incidence of overweight and obesity over 5 decades. Am J Med. 2007;120:242–250.
33. VA Management of Overweight and Obesity Working Group. VA/DoD Clinical Practice Guideline for Screening and Management of Overweight and Obesity. Washington, DC: VA Health Guidelines: US Veterans Affairs and Department of Defense; 2014.
35. Almond N, Kahwati L, Kinsinger L, et al. The prevalence of overweight and obesity among US military veterans. Mil Med. 2008;173:544–549.
36. Vimalananda VG, Miller DR, Christiansen CL, et al. Cardiovascular disease risk factors among women Veterans. J Gen Intern Med. 2013;28 (suppl 2):S517–S523.
37. Whitehead AM, Davis MB, Duvernoy C, et al. The State of Cardiovascular Health in Women Veterans. Volume 1: VA Outpatient Diagnoses and Procedures in Fiscal Year (FY) 2010. Women’s Health
Evaluation Initiative, Women’s Health
Services, Veteran’s Health Administration, Department of Veteran’s Affairs, October 2013.
38. Cohen BE, Maguen S, Bertenthal D, et al. Reproductive and other health outcomes in Iraq and Afghanistan women veterans using VA health care: association with mental health diagnoses. Womens Health Issues. 2012;22:e461–e471.
39. Burg MM, Soufer R. Post-traumatic stress disorder and cardiovascular disease. Curr Cardiol Rep. 2016;18:94.
40. Masodkar K, Johnson J, Peterson MJ. Review of posttraumatic stress disorder and obesity: exploring the link. Prim Care Companion CNS Disord. 2016;18:1.
41. Heppner PS, Lohr JB, Kash TP, et al. Metabolic syndrome: relative risk associated with post-traumatic stress disorder (PTSD) severity and antipsychotic medication use. Psychosomatics. 2012;53:550–558.
42. Bradley SM, Rumsfeld JS. Depression and cardiovascular disease. Trends Cardiovasc Med. 2015;25:614–622.
43. Shah AJ, Ghasemzadeh N, Zaragoza-Macias E, et al. Sex and age differences in the association of depression with obstructive coronary artery disease and adverse cardiovascular events. J Am Heart Assoc. 2014;3:e000741.
44. Sumner JA, Kubzansky LD, Elkind MS, et al. Exposure and posttraumatic stress disorder symptoms predict onset of cardiovascular events in women. Circulation. 2015;132:251–259.
45. Rose DE, Farmer MM, Yano EM, et al. Racial/ethnic differences in cardiovascular risk
factors among women Veterans. J Gen Intern Med. 2013;28(suppl 2):S524–S528.
Veterans/Military health; women’s health; cardiovascular risk
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