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Abstract

Background:

Females are the fastest-growing group in the veteran population, yet there is a paucity in the literature of sex-specific results from studies of chronic disease in veterans that limit our understanding of their health issues. This study provides nationally representative estimates of the physical and mental health of females and males from the Operation Enduring Freedom, Operation Iraqi Freedom, and Operation New Dawn (OEF/OIF/OND) veteran population.

Methods:

Data from the 2018 Comparative Health Assessment Interview Research Study (CHAI), a cross-sectional nationwide survey of the health and well-being of OEF/OIF/OND veterans and a comparison sample of U.S. nonveterans, were analyzed to provide sex-stratified and deployment-stratified lifetime prevalence estimates and adjusted relative odds of physical and mental health conditions in a large population-based study of OEF/OIF/OND veterans.

Results:

Overall, female veterans were significantly more likely to report cancer, respiratory disease, irritable bowel syndrome/colitis, bladder infections, vision loss, arthritis, back/neck pain, chronic fatigue syndrome, migraine, posttraumatic stress disorder, and depression. Male veterans were significantly more likely to report obesity, diabetes, heart conditions, hypertension, high cholesterol, hearing loss, fractures, spinal cord injury, sleep apnea, and traumatic brain injury. Both males and females who deployed were significantly more likely to report adverse health outcomes than those who did not deploy.

Conclusion:

This article reports sex-stratified and deployment-stratified lifetime prevalence estimates and adjusted relative odds of physical and mental health conditions in a large population-based study of OEF/OIF/OND veterans. This study demonstrates the value of epidemiological research on female veterans and its importance in understanding the burden of disease in the female veteran population.

Introduction

The number of women serving in the military has continued to increase since the 1990–1991 Gulf War,¹ with approximately 445,121 women who deployed in support of the Global War on Terrorism,² which includes Operation Enduring Freedom, Operation Iraqi Freedom, and Operation New Dawn (OEF/OIF/OND). In 2021, women accounted for 17.3% of the active-duty force and 21.4% of the reserves and National Guard.³ As a result of this increase, women are now the fastest-growing group in the veteran population, and they are estimated to account for 18% of all veterans by 2040.⁴

A 2017 review of women veterans’ health research concluded that there was a paucity of sex-specific results from studies of chronic disease in veterans.⁵ Similarly, a 2016 report by the National Academy of Sciences, Engineering, and Medicine recommended that the Secretary of the Department of Veterans Affairs (VA) determine the feasibility of evaluating sex-specific health conditions in large cohort studies of veterans.⁶ Since then, the number of studies examining these differences is growing.

There has been increasing interest in the physical health effects of deployment-related military environmental exposures (MEE) among women. In the last 5 years, there have been several published studies that explore sex-specific differences in health outcomes among 1990–1991 Gulf War and Gulf War Era Veterans in veterans who do and do not use VA health care.^7,8 While there are several studies that have reported sex-specific prevalence estimates of certain medical conditions in the OEF/OIF/OND population,^9

–14 most are limited to all veterans using VA for health care or only report on a single health condition. A 2016 article by Dursa et al. reported population-based estimates of physical and mental health among users and nonusers of VA health care; however, sex-stratified estimates were not provided as models were adjusted for sex.¹⁵

There has been a great deal of work that has examined differences by sex in mental health outcomes among OEF/OIF/OND veterans. A medical records review study by Maguen and colleagues reported that women veterans were more likely to receive a depression diagnosis than men veterans.⁹ Another study by Maguen et al. found that women veterans with posttraumatic stress disorder (PTSD) had higher health care utilization than men veterans with PTSD, an association that was magnified in the presence of comorbid depression.¹⁶ An article by Gradus et al. found that women who received a PTSD diagnosis and had a history of alcohol abuse or dependence were more likely than men to engage in nonfatal intentional self-harm.¹⁷ A mail survey of 1,207 women and 1,137 men OEF/OIF veterans found that women were more likely to report sexual harassment and probable depression than men.¹⁸ A study of suicide in OEF/OIF/OND veterans has shown different patterns of suicide risk between women and men veterans with respect to time, with men veterans having the highest suicide risk during the period of transition from military to civilian life and women having a persistent risk during and after separation from the military.¹⁹

Breland et al. conducted a medical records study of about five million VA health care users and found that the prevalence of obesity (body mass index [BMI] ≥ 30 kg/m²) was higher in women veterans (44%) than men veterans (41%), but prevalence of overweight (25 kg/m² ≤ BMI < 30 kg/m²) was lower in women veterans (31%) compared with men veterans (38%); however, among the OEF/OIF/OND veteran users obesity was higher in men (45%) than women (36%).¹⁰ Dhruva and colleagues reported that women OEF/OIF/OND veterans developed coronary artery disease and heart failure younger than men OEF/OIF/OND veterans and were less likely to be prescribed guideline-directed medication within a year of heart failure diagnosis.²⁰ VA’s Health Outcomes of Military Exposures (HOME) presented population-based lifetime estimates of respiratory disease in the National Health Study for a New Generation of U.S. Veterans and found that women OEF/OIF/OND veterans reported a higher prevalence of asthma, bronchitis, and sinusitis than men OEF/OIF/OND veterans.²¹ A study by Carlson et al., using VA medical records data, found that headache diagnoses were 1.6 times more prevalent in women OEF/OIF/OND veterans than men OEF/OIF/OND veterans.¹⁴

VA’s HOME Comparative Health Assessment Interview Research Study (CHAI) is a population-based epidemiological cohort study of OEF/OIF/OND veterans²² and provides an optimal opportunity to examine associations between sex and health outcomes in the post-9/11 veteran population. The objective of this article is to describe the physical and mental health of the CHAI study veteran population with respect to sex; the article has three specific aims: (1) provide sex-stratified lifetime prevalence estimates of physical and mental health conditions in the CHAI study population; (2) provide deployment-stratified lifetime prevalence estimates of physical and mental health conditions among female and male veterans in the CHAI study; and (3) provide estimates of the association between sex and health condition after adjusting for covariates. Overall, this article contributes to the literature by providing nationally representative estimates of the physical and mental health of females and males from the OEF/OIF/OND veteran population. One of the unique aspects of this study cohort is that it is population-based, sampled from the entire population of those who served in OEF/OIF/OND, which includes those who do not use the VA for health care. Additionally, it includes veterans who served in the era of OEF/OIF/OND but did not deploy there, which provides a comparison population. Veterans who do not use the VA for health care are understudied since they are not captured in most studies conducted by the VA, as health care data are limited to those who get their care at the VA. While there have been studies that look at sex differences in veterans, they are predominantly focused on mental health or cardiovascular disease and are only including veterans enrolled in VA health care.

Methods

Study design

The 2018 CHAI is a cross-sectional nationwide survey of the health and well-being of OEF/OIF/OND veterans and a comparison sample of U.S. nonveterans. A stratified random sampling of the U.S. Veterans Eligibility Trends and Statistics (USVETS) file²³ generated the veteran sample (n = 67,500) of adults 18 years of age and over. Females were oversampled to account for 30% of the total veteran sample. One third of the veteran sample was set aside to be surveyed if response rates fell below expected levels. Nonveterans (n = 16,843) with no prior military experience were drawn via address-based sampling from a nationally representative panel of the noninstitutionalized U.S. adult population (KnowledgePanel®).²⁴ Further details about the nonveteran comparison sample have been published elsewhere.^25
–27

In total, 38,633 veterans were asked to report about their health by completing a web-based questionnaire or a computer-assisted telephone interview via recommended methodologies.²⁸ Initial mail contacts to veterans included a $1 preincentive and an additional $50 postincentive for those who completed the survey. All participants provided informed consent prior to survey administration. Study procedures were approved by the VA Central Institutional Review Board.

The veteran response rate was 39.5% (n = 15,170 eligible, returned surveys) in the range of earlier large-scale studies of post-9/11 veterans.^18,29 Four veterans were removed because their deployment status could not be ascertained. The total analytic sample comprised 15,166 veterans (5,642 female veterans and 9,524 male veterans).

Measures

Dependent variables

Twenty-six dependent variables were examined, 25 of which comprised lifetime physical and mental health outcomes measured using the 2018 National Health Interview Survey question: “Has a doctor or other health care provider ever told you that you had any of the following conditions?”.³⁰ Respondents reported “yes” or “no” for each of the following conditions: irritable bowel syndrome (IBS)/colitis, heart condition or disease, hypertension, high cholesterol, chronic fatigue syndrome, sleep apnea, cirrhosis, hepatitis, chronic obstructive pulmonary disease (COPD)/chronic bronchitis/emphysema, asthma, sinusitis, constrictive bronchiolitis, pulmonary fibrosis, other respiratory diseases, vision or seeing problems/loss, significant hearing loss, arthritis, back/neck pain, fractures/bone or joint injury, missing limbs/amputation, spinal cord injury, traumatic brain injury (TBI), diabetes, migraine, epilepsy/seizures, frequent bladder infections, multiple sclerosis, cancer, PTSD, and depression. The six respiratory diseases were recoded into a single dichotomous variable called “respiratory disease,” representing a report of ever being diagnosed with at least one of those conditions versus never having been diagnosed with any of them. Respondents who endorsed cancer were provided an open-ended response option to specify the type of cancer. Open-ended responses were recoded as cancer or not based on consensus by three research team investigators (Y.S.C., A.I.S., E.K.D.).

Obesity, the 26th health outcome, was derived from BMI and calculated from height and weight questions^29,31 (height: “How tall are you without shoes?”, weight: “How much do you weigh without shoes? If currently pregnant, please give your usual weight before becoming pregnant”). Previously established lower and upper cut-points for height and weight¹⁰ were used (height: <48 inches versus >84 inches; weight: <74 pounds versus >700 pounds). Obesity was coded dichotomously as any level of obesity (BMI ≥ 30 kg/m²)³² versus no obesity (BMI < 30 kg/m²).

Explanatory variables

The primary explanatory variable was sex (male/female), and as mentioned above, came from the USVETS file, which was the sampling frame for this study. This file was developed by the VA’s Data Governance and Analytics business line, and the data elements included come from a variety of administrative data sources, including the Veterans Benefit Administration, the Veterans Health Administration (VHA), the Department of Defense’s (DoD) Defense Manpower Data Center, and other data sources including purchased data sources.

Deployment status was defined dichotomously as either ever having been deployed in support of OEF/OIF/OND in Iraq/Afghanistan/elsewhere or deployed not in support of this conflict (“deployed”) versus never having been deployed (“nondeployed”). Deployment data were supplemented with Gulf War roster data.³³ Additionally, military rank, branch, and component were examined. Age group (years), race/ethnicity, education, current marital status, employment status, self-reported sexual orientation (ascertained by the following question, “Do you think of yourself as”: straight or heterosexual; lesbian, gay, or homosexual; bisexual; something else), census region,³⁴ and metropolitan statistical area (MSA) were also used in the analysis. MSAs contained one or more counties with an urbanized area having a total population of at least 50,000.³⁵ Variables were based on questions derived from prior veteran studies³¹ or developed expressly for CHAI.

Statistical analyses

All statistics, except raw counts, were weighted to account for CHAI’s complex sampling design and nonresponse. Weights were further calibrated to frame totals on veteran sex and service characteristics. A resampling-based variance estimation approach (n = 200 replicate weights) employing the (n − 1) rescaling bootstrap method was applied.^36,37 The second-order Rao-Scott chi-squared test assessed the statistical significance of bivariate associations based on a design-effect-adjusted Pearson chi-squared statistic.^38,39 Domain analysis⁴⁰ provided design-based statistics for veteran subsets by sex. Overall, analytical procedures were used that considered the nonstandard features of complex surveys (e.g., unequal probabilities of selection) to minimize bias and errors in variance estimation and inference.^40
–42

Unweighted counts and weighted percentages are reported. Sex and deployment-stratified prevalence estimates were calculated for 26 health conditions. Bivariate associations were tested using contingency table analysis.^38,39 Adjusted odds ratios (AORs) and 95% confidence intervals (CIs) were calculated by regressing each health outcome onto sex controlling for deployment status, military branch, military component (active duty, reserve, national guard), military rank, age, employment status, educational status, race/ethnicity, marital status, region, and MSA. The latter were used to adjust for potential confounding. We adjusted for lifetime use of tobacco products (“In your lifetime, have you ever used cigarettes, cigars, pipes, snuff, or smokeless tobacco?”),⁴³ but its addition to our model did not change parameter estimates so it was not included. The variables applied as covariates maximized internal comparability across all 26 outcomes, as well as comparability to VA’s prior study of post-9/11 veterans¹⁵ and other sex-stratified health outcome analyses on veterans.^{13,15,18,44
–46} Tolerances were computed to investigate linear dependencies among explanatory variables; these fell within an acceptable range (>0.40).⁴⁷ The first-order interaction of sex by deployment status was tested in each model due to the possibility of differential associations by sex.^48,49 AORs exceeding 3.0, or less than 0.33, signified strong associations.⁵⁰

p-Values of ≤0.05 were considered statistically significant and adjusted via the Tukey-Kramer method to reduce Type I error inflation resulting from repeated pairwise comparisons.⁵¹ Missingness across analytic variables was <1.0%. Analyses were conducted using SAS for Linux.

Results

Baseline characteristics

Table 1 shows descriptive statistics for baseline characteristics stratified by sex. The veteran sample comprised 17.3% female and 82.7% male. Females were more likely than men to be 44 years old or younger (females versus males, 79.8% versus 72.5%), minority (44.5% versus 31.3%), bachelor’s degree recipients or higher (48.1% versus 39.7%), and residents of the South (54.0% versus 46.4%) (p < 0.001). They were less likely than males to be married (54.4% versus 65.3%), employed with pay (72.7% versus 83.4%), and to have been on active duty (63.2% versus 66.7%), or deployed (52.5% versus 74.3%) (p < 0.001). In terms of sexual orientation, more women reported being bisexual than men (5.5% versus 1.9%) and lesbian, gay, or homosexual (5.4% versus 1.8%).

Table 1.

Baseline Characteristics of Post-9/11 Female and Male Veterans (n = 15,166),^a Comparative Health Assessment Interview Research Study (CHAI)

Characteristic^b	All veterans (n = 15,166)		Females (n = 5,642, 17.3%)		Males (n = 9,524, 82.7%)
Characteristic^b	n	% (95% CI)	n	% (95% CI)	n	% (95% CI)	p ^c
Deployment status							<0.001
Deployed	10,868	70.5 (69.9–71.2)	3,592	52.5 (51.4–53.5)	7,276	74.3 (73.6–75.0)
Nondeployed	4,298	29.5 (28.8–30.1)	2,050	47.5 (46.5–48.6)	2,248	25.7 (25.0–26.4)
Military branch							<0.001
Army	7,694	50.7 (50.4–50.9)	2,837	52.7 (52.4–52.9)	4,857	50.2 (50.0–50.5)
Marine Corps	1,429	13.4 (13.2–13.6)	235	5.7 (5.5–5.9)	1,194	15.1 (14.8–15.3)
Navy/Coast Guard	2,654	17.6 (17.4–17.8)	1,122	18.8 (18.7–19.0)	1,532	17.4 (17.1–17.6)
Air Force	3,338	18.3 (18.1–18.5)	1,433	22.8 (22.6–23.1)	1,905	17.3 (17.1–17.6)
Unit component							<0.001
Active duty	9,133	66.1 (65.5–66.8)	3,319	63.2 (62.0–64.5)	5,814	66.7 (65.9–67.5)
National Guard	3,106	18.1 (17.5–18.7)	1,003	17.5 (16.4–18.6)	2,103	18.2 (17.5–19.0)
Reserve	2,927	15.8 (15.2–16.3)	1,320	19.3 (18.2–20.3)	1,607	15.0 (14.4–15.7)
Rank							0.774
Enlisted	12,990	88.2 (87.7–88.8)	4,844	88.3 (87.5–89.2)	8,146	88.2 (87.5–88.8)
Officer/warrant officer	2,175	11.8 (11.2–12.3)	798	11.7 (10.8–12.5)	1,377	11.8 (11.2–12.5)
Age group, years							<0.001
18–24	295	3.3 (3.0–3.6)	109	4.2 (3.4–4.9)	186	3.1 (2.8–3.5)
25–34	4,487	38.0 (37.4–38.5)	1,830	41.3 (40.0–42.6)	2,657	37.3 (36.6–38.0)
35–44	4,871	32.5 (31.8–33.1)	2,036	34.3 (33.0–35.5)	2,835	32.1 (31.3–32.9)
45–54	3,162	16.3 (15.8–16.9)	1,030	13.4 (12.6–14.1)	2,132	17.0 (16.3–17.6)
55–64	1,893	8.3 (7.9–8.6)	540	6.1 (5.6–6.6)	1,353	8.7 (8.3–9.1)
65 and over	458	1.6 (1.5–1.8)	97	0.8 (0.6–1.0)	361	1.8 (1.6–2.0)
Marital status
Married/domestic partner/civil union	9,777	63.4 (62.5–64.3)	3,158	54.4 (53.0–55.8)	6,619	65.3 (64.2–66.3)
Divorced/separated/widowed	2,877	16.7 (16.0–17.4)	1,444	24.6 (23.3–25.8)	1,433	15.1 (14.2–15.9)
Never married	2,475	19.9 (19.2–20.6)	1,029	21.0 (19.7–22.4)	1,446	19.7 (18.8–20.5)
Race/ethnicity							<0.001
White, non-Hispanic	9,718	66.4 (65.4–67.3)	3,150	55.5 (54.1–56.9)	6,568	68.7 (67.6–69.7)
Black, non-Hispanic	2,344	12.7 (12.0–13.3)	1,224	21.0 (19.8–22.2)	1,120	10.9 (10.2–11.6)
Other race(s), non-Hispanic	1,397	9.6 (9.0–10.2)	528	9.7 (8.7–10.6)	869	9.5 (8.8–10.2)
Hispanic	1,707	11.4 (10.8–12.0)	740	13.8 (12.8–14.8)	967	10.9 (10.2–11.6)
Sexual orientation							<0.001
Straight or heterosexual	14,256	95.6 (95.2–95.9)	5,006	88.0 (86.9–89)	9,250	97.2 (96.8–97.5)
Lesbian, gay, or homosexual	379	1.8 (1.5–2)	295	5.4 (4.7–6.1)	84	1.0 (0.8–1.2)
Bisexual	354	1.9 (1.7–2.1)	261	5.5 (4.8–6.2)	93	1.1 (0.9–1.4)
Something else	109	0.8 (0.6–0.9)	54	1.1 (0.7–1.4)	55	0.7 (0.5–0.9)
Education							<0.001
≤high school, GED	1,491	12.5 (11.9–13.2)	308	7.2 (6.4–8.0)	1,183	13.7 (12.9–14.4)
Some college/no degree	3,913	29.0 (28.1–30.0)	1,227	24.8 (23.5–26.1)	2,686	29.9 (28.8–31.1)
Associate/technical degree	2,648	17.3 (16.5–18.0)	1,087	20.0 (18.7–21.4)	1,561	16.7 (15.8–17.6)
Bachelor’s degree	3,951	24.4 (23.5–25.2)	1,655	27.3 (25.9–28.6)	2,296	23.8 (22.8–24.8)
Graduate degree	3,163	16.8 (16.2–17.4)	1,365	20.8 (19.7–21.9)	1,798	15.9 (15.2–16.6)
Employment, current							<0.001
Yes (paid employment)	11,869	81.6 (80.8–82.3)	4,060	72.7 (71.2–74.2)	7,809	83.4 (82.6–84.3)
No	3,218	18.4 (17.7–19.2)	1,555	27.3 (25.8–28.8)	1,663	16.6 (15.7–17.4)
Region							<0.001
Northeast	1,367	9.7 (9.1–10.2)	480	8.7 (7.8–9.6)	887	9.9 (9.2–10.5)
Midwest	2,765	20.0 (19.2–20.8)	907	17.3 (16.2–18.5)	1,858	20.5 (19.6–21.5)
South	7,602	47.7 (46.7–48.8)	3,063	54.0 (52.4–55.5)	4,539	46.4 (45.2–47.6)
West	3,360	22.6 (21.8–23.4)	1,158	20.0 (18.9–21.1)	2,202	23.2 (22.2–24.1)
Metropolitan statistical area							0.009
Yes	12,790	83.8 (83.1–84.5)	4,835	85.3 (84.1–86.4)	7,955	83.5 (82.8–84.3)
No	2,328	16.2 (15.5–16.9)	782	14.7 (13.6–15.9)	1,546	16.5 (15.7–17.2)

Weighted statistics except for counts.

Self-reported, there are missing data.

Bolded values are statistically significant at p ≤ 0.05. Based on design-adjusted Rao-Scott chi-square test.

CI, confidence interval; GED, General Education Diploma.

Sex-stratified prevalence estimates

Table 2 shows the sex-stratified prevalence estimates of 26 health conditions. For nearly half (n = 11) of the 26 conditions, the prevalence estimates were significantly greater for females than males for cancer (4.7% versus 3.4%), respiratory disease (32.2% versus 21.9%), IBS/colitis (14.3% versus 9.3%), bladder infections (7.9% versus 0.8%), vision loss (43.2% versus 35.0%), chronic fatigue syndrome (5.8% versus 4.0%), migraine (33.4% versus 16.1%), PTSD (26.3% versus 23.3%), depression (43.0% versus 25.1%) (p < 0.001), arthritis (27.8% versus 25.8%) (p = 0.007) and back/neck pain (51.2% versus 49.0%) (p = 0.021). For males, the prevalence estimates of the following 10 conditions were significantly greater than that found for females: obesity (current, 41.0% versus 34.4%), diabetes (5.1% versus 3.8%), hypertension (29.8% versus 18.6%), high cholesterol (28.5% versus 19.3%), hearing loss (10.9% versus 4.8%), fractures/bone/joint injury (49.1% versus 40.9%), spinal cord injury (6.0% versus 3.0%), sleep apnea (23.0% versus 10.1%), TBI (7.5% versus 4.0%) (p < 0.001), and heart conditions (6.8% versus 5.8%) (p = 0.027).

Table 2.

Gender-Stratified Lifetime Prevalence Estimates of Physical and Mental Health Conditions among Post-9/11 Veterans (n = 15,166),^a Comparative Health Assessment Interview Research Study (CHAI)

	All veterans (n = 15,166)		Female (n = 5,642, 17.3%)		Male (n = 9,524, 82.7%)
Health outcome^b	n	% (95% CI)	n	% (95% CI)	n	% (95% CI)	p ^c
Obesity^d	5,973	39.9 (38.9–40.8)	1,969	34.4 (32.8–36.0)	4,004	41.0 (39.9–42.1)	<0.001
Diabetes	951	4.8 (4.5–5.2)	264	3.8 (3.3–4.3)	687	5.1 (4.6–5.5)	<0.001
Hypertension	4,446	27.8 (27.0–28.7)	1,201	18.6 (17.5–19.6)	3,245	29.8 (28.8–30.7)	<0.001
Heart condition	1,172	6.6 (6.2–7.0)	353	5.8 (5.2–6.5)	819	6.8 (6.3–7.2)	0.027
High cholesterol	4,560	26.9 (26.1–27.8)	1,305	19.3 (18.3–20.4)	3,255	28.5 (27.6–29.5)	<0.001
Cancer	811	3.6 (3.3–3.9)	335	4.7 (4.0–5.3)	476	3.4 (3.0–3.8)	<0.001
Respiratory disease^e	4,207	23.7 (22.9–24.5)	1,960	32.2 (30.7–33.6)	2,247	21.9 (21.0–22.8)	<0.001
Cirrhosis	62	0.4 (0.3–0.6)	16	0.3 (0.1–0.5)	46	0.5 (0.4–0.6)	0.095
Hepatitis	191	1.1 (0.9–1.3)	60	1.0 (0.7–1.3)	131	1.2 (0.9–1.4)	0.261
IBS/colitis	1,746	10.2 (9.5–10.8)	863	14.3 (13.3–15.3)	883	9.3 (8.6–10.0)	<0.001
Bladder infections	541	2.0 (1.8–2.2)	457	7.9 (7.0–8.7)	84	0.8 (0.6–1.0)	<0.001
Vision loss	6,252	36.4 (35.5–37.4)	2,535	43.2 (41.6–44.8)	3,717	35.0 (33.9–36.1)	<0.001
Hearing loss	1,550	9.9 (9.3–10.4)	317	4.8 (4.1–5.4)	1,233	10.9 (10.3–11.6)	<.001
Arthritis	4,713	26.2 (25.3–27.0)	1,823	27.8 (26.6–29.0)	2,890	25.8 (24.9–26.8)	0.007
Back/neck pain	8,031	49.3 (48.4–50.3)	3,103	51.2 (49.6–52.8)	4,928	49.0 (47.9–50.1)	0.021
Fractures, bone/joint injury	7,222	47.6 (46.7–48.6)	2,402	40.9 (39.3–42.4)	4,820	49.1 (47.9–50.2)	<0.001
Spinal cord injury	771	5.5 (5.1–5.9)	183	3.0 (2.5–3.5)	588	6.0 (5.5–6.5)	<0.001
Missing limbs/amputation	106	0.7 (0.5–0.8)	30	0.5 (0.3–0.7)	76	0.7 (0.5–0.9)	0.082
Sleep apnea	3,187	20.8 (20.0–21.6)	679	10.1 (9.3–10.9)	2,508	23.0 (22.1–24.0)	<0.001
Chronic fatigue syndrome	770	4.3 (3.9–4.7)	366	5.8 (5.1–6.5)	404	4.0 (3.5–4.4)	<0.001
Multiple sclerosis	72	0.4 (0.3–0.5)	37	0.6 (0.3–0.8)	35	0.3 (0.2–0.4)	0.054
TBI	912	6.9 (6.4–7.4)	248	4.0 (3.4–4.5)	664	7.5 (6.9–8.2)	<0.001
Epilepsy/seizures	231	1.5 (1.2–1.7)	99	1.8 (1.4–2.3)	132	1.4 (1.1–1.7)	0.089
Migraine	3,460	19.1 (18.4–19.8)	1,944	33.4 (32.1–34.8)	1,516	16.1 (15.3–16.9)	<0.001
PTSD	3,557	23.8 (23.0–24.6)	1,519	26.3 (24.9–27.7)	2,038	23.3 (22.3–24.3)	<0.001
Depression	4,641	28.2 (27.3–29.2)	2,389	43.0 (41.4–44.6)	2,252	25.1 (24.1–26.2)	<0.001

Weighted statistics except for counts.

Percent based on number of respondents for specific health outcome/condition.

Bolded values were statistically significant at p ≤ 0.05. Based on design-adjusted Rao-Scott chi-square test.

Obesity is body mass index (BMI) ≥ 30 kg/m² that was based on current, self-reported height and weight. Missing (n = 126). Mean BMI for females was 27.9 (SEM = 0.010) and 29.0 (SEM = 0.060) for males. Mean BMI was significantly greater (p < 0.001) for males than females.

Respiratory disease was at least one report of the following: chronic obstructive pulmonary disease/chronic bronchitis/emphysema, asthma, sinusitis, constrictive bronchiolitis, pulmonary fibrosis, and other respiratory diseases.

CI, confidence interval; IBS, irritable bowel syndrome; PTSD, posttraumatic stress disorder; TBI, traumatic brain injury.

Deployment-stratified prevalence estimates in men and women

Table 3 provides the deployment-stratified prevalence estimates for the 26 health conditions for female and male veterans, respectively. For nearly 75% of conditions (n = 18) in females and males, respectively, prevalence estimates were significantly (p ≤ 0.034) greater for the deployed versus the nondeployed. However, only among males, the prevalence estimates of current obesity were greater for the deployed than the nondeployed (43.5% versus 33.7%) (p < 0.001), while the prevalence estimate of epilepsy/seizures was significantly lower for the deployed (1.2% versus 1.9%) (p = 0.044).

Table 3.

Deployment-Stratified Lifetime Prevalence Proportion Estimates of Physical and Mental Health Conditions Among Female and Male Post-9/11 Veterans (n = 15,166),^a Comparative Health Assessment Interview Research Study (CHAI)

	Female (n = 5,642, 17.3%)					Male (n = 9,524, 82.7%)
	Deployed (n = 3,592, 52.5%)		Nondeployed (n = 2,050, 47.5%)			Deployed (n = 7,276, 74.3%)		Nondeployed (n = 2,248, 25.7%)
Health outcome^b	n	% (95% CI)	n	% (95% CI)	p ^c	n	% (95% CI)	n	% (95% CI)	p ^c
Obesity^d	1,289	35.7 (33.9–37.4)	680	33.0 (30.5–35.5)	0.058	3,196	43.5 (42.3–44.8)	808	33.7 (31.6–35.8)	<0.001
Diabetes	178	4.4 (3.7–5.2)	86	3.1 (2.4–3.8)	0.008	578	5.8 (5.3–6.3)	109	2.9 (2.2–3.5)	<0.001
Hypertension	821	21.3 (19.9–22.7)	380	15.5 (13.9–17.2)	<0.001	2,698	33.1 (32.0–34.2)	547	20.1 (18.2–22.0)	<0.001
Heart condition	241	6.6 (5.7–7.4)	112	5.0 (4.0–6.1)	0.034	691	7.6 (7.0–8.2)	128	4.3 (3.5–5.2)	<0.001
High cholesterol	934	23.9 (22.5–25.3)	371	14.3 (12.5–16.0)	<0.001	2,729	32.6 (31.5–33.8)	526	16.7 (15.2–18.1)	<0.001
Cancer	232	5.5 (4.7–6.4)	103	3.7 (2.8–4.6)	0.003	412	4.0 (3.6–4.5)	64	1.6 (1.1–2.0)	<0.001
Respiratory disease^e	1,309	35.1 (33.3–36.8)	651	29.0 (26.8–31.3)	<0.001	1,815	23.3 (22.2–24.4)	432	17.9 (16.2–19.5)	<0.001
Cirrhosis	11	0.3 (0.2–0.5)	5	0.2 (0.0–0.5)	0.459	38	0.5 (0.3–0.7)	8	0.4 (0.1–0.7)	0.667
Hepatitis	43	1.1 (0.7–1.5)	17	0.8 (0.3–1.2)	0.265	108	1.3 (1.0–1.5)	23	0.9 (0.5–1.3)	0.187
IBS/colitis	594	15.9 (14.6–17.3)	269	12.5 (10.9–14.1)	0.001	712	10.1 (9.2–11.0)	171	7.0 (5.9–8.2)	<0.001
Bladder infections	304	8.2 (7.2–9.2)	153	7.5 (6.2–8.8)	0.400	66	0.9 (0.6–1.1)	18	0.6 (0.3–1.0)	0.338
Vision loss	1,654	45.1 (43.1–47.0)	881	41.1 (38.4–43.9)	0.020	3,000	37.4 (36.1–38.7)	717	28.1 (26.2–30.0)	<0.001
Hearing loss	232	6.1 (5.2–7.0)	85	3.4 (2.5–4.3)	<0.001	1,086	13.1 (12.3–14.0)	147	4.6 (3.6–5.6)	<0.001
Arthritis	1,337	35.4 (33.7–37.0)	486	19.4 (17.6–21.2)	<0.001	2,485	30.1 (28.9–31.3)	405	13.6 (12.1–15.2)	<0.001
Back/neck pain	2,147	58.1 (56.2–59.9)	956	43.6 (41.0–46.1)	<0.001	4,075	54.1 (52.8–55.4)	853	34.0 (31.7–36.3)	<0.001
Fractures, bone/joint injury	1,619	44.0 (42.1–45.8)	783	37.4 (35.0–39.9)	<0.001	3,846	51.5 (50.2–52.9)	974	41.8 (39.6–44.0)	<0.001
Spinal cord injury	123	3.3 (2.7–3.9)	60	2.7 (1.9–3.5)	0.201	496	6.7 (6.1–7.2)	92	4.1 (3.2–5.0)	<0.001
Missing limbs/amputation	25	0.7 (0.4–1.0)	5	0.2 (0.0–0.5)	0.012	61	0.7 (0.5–0.9)	15	0.7 (0.3–1.0)	0.716
Sleep apnea	511	13.2 (11.9–14.4)	168	6.7 (5.6–7.8)	<0.001	2,143	26.5 (25.4–27.7)	365	12.8 (11.3–14.4)	<0.001
Chronic fatigue syndrome	261	6.9 (6.0–7.8)	105	4.6 (3.6–5.7)	0.001	358	4.6 (4.1–5.2)	46	2.0 (1.3–2.7)	<0.001
Multiple sclerosis	22	0.5 (0.3–0.8)	15	0.6 (0.2–1.0)	0.785	26	0.3 (0.2–0.4)	9	0.3 (0.1–0.6)	0.952
TBI	198	5.5 (4.7–6.3)	50	2.3 (1.5–3.0)	<0.001	593	9.1 (8.3–9.9)	71	2.9 (2.1–3.7)	<0.001
Epilepsy/seizures	58	1.6 (1.2–2.1)	41	2.1 (1.3–2.9)	0.370	90	1.2 (0.9–1.5)	42	1.9 (1.3–2.5)	0.044
Migraine	1,295	35.6 (34.0–37.2)	649	31.1 (28.7–33.4)	0.001	1,247	17.6 (16.7–18.6)	269	11.6 (10.2–13.0)	<0.001
PTSD	1,128	31.9 (30.1–33.6)	391	20.1 (18.1–22.1)	<0.001	1,823	28.0 (26.8–29.2)	215	9.7 (8.4–11.0)	<0.001
Depression	1,549	43.8 (42.0–45.6)	840	42.2 (39.7–44.6)	0.256	1,752	25.5 (24.3–26.7)	500	24.1 (22.0–26.3)	0.257

Weighted statistics presented except for counts.

Percent based on number of respondents for specific health outcome/condition.

Bolded values were statistically significant at p ≤ 0.05. Based on the design-adjusted Rao-Scott chi-square test.

Obesity is body mass index (BMI) ≥ 30 kg/m² that was based on current, self-reported height and weight. Missing (n = 126). The mean BMI for females was 27.9 (SEM = 0.010) and 29.0 (SEM = 0.060) for males. The mean BMI was significantly greater (p < 0.001) for males than females.

CI, confidence interval; IBS, irritable bowel syndrome; PTSD, posttraumatic stress disorder; TBI, traumatic brain injury.

The prevalence estimate among deployed females was at least 1.5 times that for deployed males for respiratory disease (35.1% versus 23.3%), IBS/colitis (15.9% versus 10.1%), bladder infections (8.2% versus 0.9%), chronic fatigue syndrome (6.9% versus 4.6%), multiple sclerosis (0.5% versus 0.3%), migraine (35.6% versus 17.6%), and depression (43.8% versus 25.5%) (Table 3). Differences of this magnitude for deployed males versus deployed females were found for hypertension (33.1% versus 21.3%), hearing loss (13.1% versus 6.1%), spinal cord injury (6.7% versus 3.3%), and TBI (9.1% versus 5.5%).

Multivariable adjusted associations

Table 4 presents AORs for associations between each of the 26 health outcomes. The odds of diabetes among males were 1.2 times higher than those found for females after adjusting for other covariates (AOR = 1.24, 95% CI: 1.01–1.52, p < 0.05). Other health conditions found to be significantly (p < 0.001) elevated for males relative to females were hearing loss (AOR = 1.88, 95% CI: 1.56–2.28), high cholesterol (AOR = 1.53, 95% CI: 1.39–1.68), fractures/bone/joint injury (AOR = 1.27, 95% CI: 1.16–1.39), sleep apnea (AOR = 2.81, 95% CI: 2.47–3.19), and TBI (AOR = 1.69, 95% CI: 1.42–2.01). Among females, the odds of bladder infections were significantly higher (p < 0.001) than those for males (males versus females: AOR = 0.09, 95% CI: 0.07–0.13). Other conditions significantly (p < 0.001) elevated among females were cancer (AOR = 0.50, 95% CI: 0.40–0.61), respiratory disease (AOR = 0.59, 95% CI: 0.54–0.65), IBS/colitis (AOR = 0.64, 95% CI: 0.57–0.72), vision loss (AOR = 0.66, 95% CI: 0.61–0.73), arthritis (AOR = 0.74, 95% CI: 0.67–0.81), back/neck pain (AOR = 0.79, 95% CI: 0.73–0.86), chronic fatigue syndrome (AOR = 0.71, 95% CI: 0.58–0.88), and depression (AOR = 0.50, 95% CI: 0.45–0.55).

Table 4.

Effect Size for Associations Between Health Outcome and Gender After Adjusting for Covariates^a Including the Interaction by Deployment Status, Comparative Health Assessment Interview Research Study (CHAI)

		Interaction of gender X deployment status^b
Health outcome	Males:females	Among femalesDeployed:nondeployed	Among malesDeployed:nondeployed	p
	AOR (95% CI)
Obesity^c	—^d	1.03 (0.90–1.18)	1.31 (1.16–1.48) ^***	0.008
Diabetes	1.24 (1.01–1.52) ^*	—	—	0.234
Hypertension	—	0.98 (0.82–1.17)	1.33 (1.16–1.52) ^***	0.044
Heart condition	1.14 (0.97–1.34)	—	—	0.230
High cholesterol	1.53 (1.39–1.68) ^***	—	—	0.224
Cancer	0.50 (0.40–0.61) ^***	—	—	0.170
Respiratory disease^e	0.59 (0.54–0.65) ^***	—	—	0.995
Cirrhosis	1.47 (0.69–3.13)	—	—	0.667
Hepatitis	1.34 (0.83–2.17)	—	—	0.770
IBS/colitis	0.64 (0.57–0.72) ^***	—	—	0.750
Bladder infections	0.09 (0.07–0.13) ^***	—	—	0.876
Vision loss	0.66 (0.61–0.73) ^***	—	—	0.056
Hearing loss	1.88 (1.56–2.28) ^***	—	—	0.054
Arthritis	0.74 (0.67–0.81) ^***	—	—	0.930
Back/neck pain	0.79 (0.73–0.86) ^***	—	—	0.145
Fractures, bone/joint injury	1.27 (1.16–1.39) ^***	—	—	0.496
Spinal cord injury	2.03 (1.63–2.52) ^***	—	—	0.168
Missing limbs/amputation	1.21 (0.70–2.08)	—	—	0.115
Sleep apnea	2.81 (2.47–3.19) ^***	—	—	0.593
Chronic fatigue syndrome	0.71 (0.58–0.88) ^***	—	—	0.084
Multiple sclerosis	0.63 (0.33–1.22)	—	—	0.890
TBI	1.69 (1.42–2.01) ^***	—	—	0.278
Epilepsy/seizures	0.98 (0.68–1.42)	—	—	0.493
Migraine	—	1.02 (0.89–1.17)	1.47 (1.25–1.74) ^***	0.033
PTSD	—	1.92 (1.64–2.26) ^***	4.21 (3.55–4.98) ^***	<0.001
Depression	0.50 (0.45–0.55) ^***	—	—	0.950

Adjusted for deployment status, military branch, military component, rank, age, employment status, educational status, race/ethnicity, marital status, region, and metropolitan statistical area. Weighted statistics presented. Statistically significant results were bolded.

Interactions based on associations between health outcome and gender among deployed and nondeployed veterans, respectively: obesity, ND, M:F, 1.07 (0.90–1.27)/D, 1.44 (1.29–1.61)***; hypertension, ND, M:F, 1.51 (1.23–1.86)***/D, 2.00 (1.79–2.24)***; migraine, ND, M:F, 0.31 (0.26–0.38)***/D, 0.41 (0.37–0.46)***; PTSD, ND, M:F, 0.49 (0.40–.61)***/D, 0.95 (0.83–1.08).

Obesity is body mass index (BMI) ≥ 30 kg/m² that was based on current, self-reported height and weight. Missing (n = 126).

(—) Either no significant interaction for that association was found (only main effects presented) or a significant interaction was found (only interaction effects presented).

p < 0.05.

p < 0.01.

***

p < 0.001.

AOR, adjusted odds ratio; CI, confidence interval; D, deployed; F, females; IBS, irritable bowel syndrome; M, males; ND, nondeployed; PTSD, posttraumatic stress disorder; TBI, traumatic brain injury.

Interactions

Table 4 presents effect sizes for the following significant interactions: obesity (p = 0.008), hypertension (p = 0.044), migraine (p = 0.033), and PTSD (p < 0.001). The odds of obesity among deployed veterans were 1.3 times those for nondeployed veterans after adjusting for covariates (AOR = 1.31, 95% CI: 1.16–1.48) (p < 0.001); no difference by deployment status was demonstrated for females. Hypertension was significantly greater (p < 0.001) for deployed versus nondeployed males (AOR = 1.33, 95% CI: 1.16–1.52) but not for females. The odds of migraine among deployed males were nearly 1.5 times those for the nondeployed (AOR = 1.47, 95% CI: 1.25–1.74, p < 0.001), a finding absent for females. Furthermore, the association between PTSD and deployment status among males (AOR = 4.21, 95% CI: 3.55–4.98, p < 0.001) was greater than 1.5 times the association among females (AOR = 1.92, 95% CI: 1.64–2.26, p < 0.001).

Discussion

This article reports sex-stratified and deployment-stratified lifetime prevalence estimates and adjusted relative odds of physical and mental health conditions in a large population-based study of OEF/OIF/OND veterans. Overall, female veterans were significantly more likely than male veterans to report cancer, respiratory disease, IBS/colitis, bladder infections, vision loss, arthritis, back/neck pain, chronic fatigue syndrome, migraine, PTSD, and depression. Male veterans were significantly more likely than female veterans to report obesity, diabetes, heart conditions, hypertension, high cholesterol, hearing loss, fractures, spinal cord injury, sleep apnea, and TBI. Among both female and male veterans, those who deployed were significantly more likely to report adverse health outcomes than those who did not deploy for almost all physical and mental conditions; however, controlling for deployment made little impact on the adjusted associations between males and females except for obesity, hypertension, migraine, and PTSD.

We found in our study population that obesity was significantly higher among male veterans than females (41.0% versus 34.4%, respectively). This is consistent with findings from a study of obesity among VHA users by Breland et al. that reported a 45% obesity prevalence among men OEF/OIF/OND veterans and 36% among OEF/OIF/OND women veterans.¹⁰ In addition, male OEF/OIF/OND veterans in our study were significantly more likely to have other metabolic syndrome-related conditions than female OEF/OIF/OND veterans including diabetes, hypertension, high cholesterol, and heart disease. This trend is consistent with what is observed in the nonveteran population where metabolic syndrome-related conditions are higher in men than in women,^52

–58 which may vary, for example, by age (e.g., women: menopausal versus nonmenopausal) or variant of the condition (e.g., type 1 versus type 2 diabetes).^54,55,59 Furthermore, after adjusting for deployment status, no difference was shown between males and females for heart conditions, which may be related to increasing rates of coronary heart disease in women, particularly those 35–54 years of age.⁵⁹ Researchers stress the need for further research on cardiovascular disease in women veterans given the growing comparability of their combat and other service-related exposures to those of men^59
–61 and to other factors such as military sexual trauma.^62,63

Overall, the prevalence of sleep apnea was significantly higher among male veterans than female veterans after adjustment and may be related to obesity, given its relationship to sleep apnea.^64
–66 However, it should be noted that when stratified by deployment status in our analysis, the prevalence of sleep apnea was higher in the deployed groups, for both males and females. We postulate that this may be related to co-occurring PTSD, as sleep-disordered breathing has been shown to be elevated in veterans with PTSD,^67
–69 and PTSD is higher among veterans who deployed to OEF/OIF/OND compared with those who did not.^70,71 This demonstrates an important public health issue for OEF/OIF/OND veterans as there is evidence to suggest that metabolic disorders can make sleep apnea worse, leading to a bidirectional relationship.⁷² Strategies to reduce obesity and metabolic disorders among veterans are needed to reduce morbidity and costs associated with sleep apnea.

In this study, female veterans were significantly more likely to report respiratory disease than male veterans, even after adjustment for deployment and lifetime use of tobacco products (not reported in tables); in fact, nondeployed female veterans had a higher prevalence of respiratory disease than deployed males (29.0% versus 23.3%). This is consistent with both veteran literature^7,21 and nonveteran literature.^73,74 In a large population-based study of OEF/OIF veterans published by Barth et al., women veterans reported more respiratory disease diagnoses than men.²¹ This same trend was reported in a study by Dursa et al. in the 1990–1991 Gulf War veteran population, where women in the Gulf War (deployed) and Gulf War era (nondeployed) reported a higher prevalence of asthma and COPD than men.⁷ However, it should be noted that there is mounting evidence that pulmonary diseases impact women differently and more severely than they do men,⁷⁵ and this is hypothesized to be due to hormonal signaling and the immune system proteome.^76,77

The migraine findings were interesting. Overall, female veterans, both deployed and nondeployed, reported a high prevalence of migraine headaches, which has been reported for women in other studies of veterans^7,78 and women civilians.^79,80 However, we found a significant interaction by deployment status among males in this study, where deployment increased the adjusted odds of migraine almost 1.5 times. This effect was not present in females. We postulate that this may be related to TBI, as the prevalence of TBI was much higher in the deployed males, and migraine is a known sequela of TBI.^81
–83

The sex differences in the prevalence and presentation of musculoskeletal disorders were notable. Arthritis and back and neck pain were more common in females, whereas fractures, bone/joint injury, and spinal cord injury were more prevalent in male veterans. A large administrative records study of OEF/OIF veteran VA health care users by Haskell and colleagues found that women were more likely to be diagnosed with back problems and musculoskeletal problems,¹³ and another study found that women OEF/OIF veterans were more likely than men to receive a musculoskeletal service-connected disability.⁸⁴ In recent years, the military has made efforts to design body armor specifically for women, acknowledging the increase in the number of women in the service and the need for properly fitted equipment.^85,86 Women-specific body armor was not used during the wars in Iraq and Afghanistan, and this may contribute to the observed differences in musculoskeletal disorders in our study, as ill-fitting, heavy equipment designed for men may add additional stress to women service members’ bodies. Pain has long been recognized as a comorbid condition of PTSD^87

–90 and depression^91,92 in veterans. Given the high reporting of PTSD and depression among females in this study and the known relationship with pain, it is possible that this may be partially responsible for our findings.

Limitations and strengths of the study should be noted. This was a retrospective, cross-sectional study, and thus causality was not assessed. Data were self-reported and subject to measurement error including recall bias. Since the questions used to calculate prevalence asked about the diagnosis of medical conditions, cases of medical conditions that have not been diagnosed would not be captured, possibly leading to an underestimate of the true population prevalence. In our definition of the deployed, we included veterans who were deployed but not to Iraq/Afghanistan in support of OEF/OIF/OND. This may have negated effects from deployment-related exposures.

The sex variable used in this study came from the USVETS file, this file enumerates all veterans (over 38 million), and the information file comes from DoD and other federal sources. The sex variable used in the analysis was derived from this file, it was not self-reported. There is a possibility that there could have been an administrative error with this variable and veterans’ sex could have been misclassified. Self-reported gender identity was assessed in the survey with the following question, “What is your current gender identity? (Male; Female; Transgender Male/Trans Man/FTM; Transgender Female/Trans Female/MTF; Gender non-conforming; Different Identity).” While we understand that sex and gender identity are not the same, we performed analyses to determine the agreement between these two variables, and the agreement was 98.7%, suggesting that misclassification was minimal.

Importantly, this study’s major strength is that it is the first to report sex- and deployment-stratified prevalence estimates based on data generated from a large population-based cohort of OEF/OIF/OND veterans—users and nonusers of VA health care. We performed data linkages to the VHA encounter data and found that 38% of the respondents had never had an encounter in VHA. We also adjusted for sociodemographic and military characteristics and applied analytic procedures that accounted for CHAI’s complex survey design. Data were weighted to maximize the representativeness and generalizability of estimates to the broader OEF/OIF/OND veteran population.

Conclusions

Footnotes

Acknowledgments

The authors would like to thank the veterans who participated in the CHAI study because this information could not be disseminated without their responses. The authors would also like to thank the VA Central Office librarian staff, who retrieved many of the articles needed in support of the article.

Authors’ Contributions

E.K.D., Y.S.C., and P.A.B. contributed to the study design, data analysis, interpretation of the results, and writing of the article. A.I.S. designed the CHAI study, supervised its administration, and critically reviewed the article. W.J.C. provided a critical review and revision of the article. All authors read and approved the final article.

Author Disclosure Statement

The authors declare that they have no competing interests.

Funding Information

This study was funded by the Health Outcomes Military Exposures (HOME), Epidemiology Program, Office of Patient Care Services, U.S. Department of Veterans Affairs.

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United States General Accounting Office. Women in the Military: Deployment in the Persian Gulf War. 1993. GAO/NSIAD-93-93. Available from: https://www.gao.gov/assets/nsiad-93-93.pdf

United States Department of Defense (DoD) and United States Department of Veterans Affairs (VA). VA/DoD Identity Repository (VADIR). Availble from: https://www.hmisrepository.va.gov

United States Departmen of Defense. Department of Defense Releases Annual Demographics Report—Upward Trend in Number of Women Serving Continues. [Last accessed November 2023 ].

Department of Veterans Affairs Women Veterans Health Care: Facts and Statistics. Available from: https://www.womenshealth.va.gov/WOMENSHEALTH/materials-and-resources/facts-and-statistics.asp

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The Physical and Mental Health of Post-9/11 Female and Male Veterans: Findings from the Comparative Health Assessment Interview Research Study

Abstract

Background:

Methods:

Results:

Conclusion:

Introduction

Methods

Study design

Measures

Dependent variables

Explanatory variables

Statistical analyses

Results

Baseline characteristics

Sex-stratified prevalence estimates

Deployment-stratified prevalence estimates in men and women

Multivariable adjusted associations

Interactions

Discussion

Conclusions

Footnotes

Acknowledgments

Authors’ Contributions

Author Disclosure Statement

Funding Information

References