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INTRODUCTION: Little is known about the geographical distribution of cigarette use among military service members and veterans. In this study, we estimated state-specific rates of current cigarette use for service members and veterans and compared these to the current cigarette use rates of civilians. METHODS: We used data from the 2017 Behavioral Risk Factor Surveillance System to generate survey-weighted percentages with 95% confidence intervals of current cigarette use among service members and veterans (SMVs) and civilians. Respondents (n=450016) were classified as an SMV if they answered in the affirmative to the following question: 'Have you ever served on active duty in the United States Armed Forces, either in the regular military or in a National Guard or military reserve unit?'. Current cigarette users were persons who reported having smoked 100 cigarettes in their lifetime and smoked 'some days' or 'every day' at the administration of the survey. RESULTS: Nationally, 17.3% (95% CI: 16.6–18.0) of SMVs reported current cigarette use, while 16.2% (95% CI: 16.0–16.5) of civilians reported current cigarette use. By state, current cigarette use rates ranged from 10.0% in Utah (95% CI: 7.5–12.5) to 23.7% in Indiana (95% CI: 20.9–26.5) among service members and veterans, and from 8.8% in Utah (95% CI: 8.0–9.6) to 27.0% in West Virginia (95% CI: 25.3–28.6) among civilians. CONCLUSIONS: Resources and interventions directed at cigarette smoking cessation should consider military status and geography when recruiting participants.

Book review of Brave, Strong, True: The Modern Warrior's battle for Balance by Dr. Kate Hendricks Thomas.

LAY SUMMARY A national survey of U.S. military service members and civilians aged 18-20 years found that military service members were less likely than their civilian peers to use alcohol if they lived in a state with a Tobacco21 (T21) policy. Given that individuals who smoke are also more likely to use alcohol, the analysis shows that tobacco policies may also affect alcohol use behaviors for young adult military service members.

Introduction: Previous studies have shown that breast cancer incidence rates are higher among female Veterans than the general population due to factors such as increased lifetime exposure to breast cancer risk factors or more accurate detection and surveillance. The present study explored relationships between nationally representative county-level breast cancer outcomes, mammography screening rates, female Veteran population density, and social vulnerability. Methods: Data for the present ecological study were obtained at the county level from the United States Census Bureau, the University of South Carolina's Hazards and Vulnerability Research Institute (HVRI), and the National Cancer Institute. We conducted ordinary least squares (OLS) multiple regression analyses to determine the relative influence of female Veteran population density, social vulnerability, and mammography screening rates on breast cancer incidence and mortality rates between 2010 and 2014. County-level covariates such as liquor store density, cigarette smoking prevalence, air pollution, and access to healthy foods, were entered into each model to determine the unique influence of each of the main study variables on breast cancer outcomes. Results: County-level breast cancer incidence rates were higher in counties with greater female Veteran population density, lower social vulnerability, and higher mammography screening rates ( n=2,698, F=33.669, p<0.001). County-level breast cancer mortality rates were higher in counties with lower female Veteran population density, higher social vulnerability, and lower mammography screening rates ( n=1,803, F=18.180, p<0.001). Discussion: The results of the present exploratory study were preliminary, and thus further research on relationships examined in this study are needed. However, because female Veterans were shown to live in counties with relatively high mammography screening rates and lower social vulnerability, their risk for mortality from breast cancer may be lower than for the general population – in particular due to early detection and treatment.

Although the literature on veteran differences in science, technology, engineering, and mathematics (STEM) occupational outcomes by gender is established and veteran/nonveteran differences in STEM outcomes are well studied, we fill a gap in the literature by examining the following two research questions in this study: (1) are rural veterans less likely than urban veterans to be employed in a STEM occupation and how does race/ethnicity modify this relationship; (2) among veterans in a STEM occupation, does total income vary by rural/urban location and race/ethnicity? We retrieved data on employed military veterans ( n = 845,467) aged 18 to 65 years from the 2008–2020 American Community Survey. Results showed that rural-dwelling Black and Hispanic veterans were less likely than Whites to be employed in a STEM field. Among veterans employed in a STEM field, rural-dwelling Hispanics had lower annual incomes than Whites. As such, future STEM education programs should target rural-dwelling veterans of color.

Some research has shown that Lyme disease cases among U.S. military veterans have increased since the early 2000s. The purpose of the present study was to determine whether high concentrations of military veterans live in areas where Lyme disease is hyper-endemic. Lyme disease case-report data for 2015 were retrieved at the county-level from the Centers for Disease Control and Prevention. Veteran population density at the county level was determined using data from the U.S. Census. County control variables, such as weather patterns, forestation, and socioeconomic conditions were retrieved from various sources. Multiple linear regression was used to examine associations between variables. After controlling for county-level environmental and social conditions, results showed that military veteran population density was positively associated with Lyme disease incidence rates. Military veterans, due to their choice of geographic residence and recreation, may be a population at risk for developing Lyme disease.

Some research shows that physical activity levels are low among veterans, but research gaps exist specifically in regards to promoting physical activity in veterans with multiple morbidities. For the present study, we retrieved data from the 2015 Behavioral Risk Factor Surveillance System. The study sample included 57,842 military service members and veterans. We carried out a mediation analysis to determine the effect of social support on the relationship between multiple morbidities and aerobic physical activity. Social support partially mediated the relationship between the presence of multiple morbidities and aerobic physical activity, a*b= -0.003, [95% CI = -0.007, -0.001]. Programs aimed at facilitating adequate social support among service members and veterans with multiple morbidities may increase their uptake of aerobic physical activity, and thus, decrease concomitant risk for health-related disorders.

Introduction:To better understand depression in United States (US) servicewomen, needs assessment data from the Service Women's Action Network (SWAN) were collected and analyzed, with comparison samples drawn from the Centers for Disease Control and Prevention (CDC) Behavioral Risk Factor Surveillance System (BRFSS). The purpose of the present study was threefold. First, an assessment of the spatial distribution of depression in the United States among military women was made using geographic information systems. Second, the authors sought to determine differences in the prevalence of undiagnosed mental health concerns and diagnosed depression in women by military service status. Third, the authors sought to identify risk factors for depression among military women. Methods: Frequencies and percentages for all demographic, geographic, and outcome variables were calculated by military service status and data source. Differences among three groups – non-Veteran respondents of the BRFSS, Veteran respondents of the BRFSS, and SWAN member Veterans – were analyzed with the Chi-square test of independence. Estimates of the state-level prevalence of undiagnosed mental health concerns and diagnosed depression among military women who responded to either the 2016 BRFSS or the 2017 SWAN needs assessment were calculated and represented with state-boundary choropleth maps in Quantum GIS (QGIS). Results: A multinomial logistic regression model, adjusted for educational attainment, race, ethnicity, employment status, US region, and rurality, showed that military women and women Veterans were more likely to have undiagnosed mental health concerns and diagnosed depression, χ2 28 = 4,891.91, p < 0.001, Nagelkerke's R2 = 0.03. Spatial analysis indicated that respondents living in the South were more likely to have diagnosed depression or undiagnosed mental health symptoms in both the BRFSS and SWAN needs assessment samples. Discussion: Primary findings from this study suggest that given the regional variation in depression among women Veterans, future studies should work to examine the role of the region in mental health for servicewomen in the United States, looking at available services and cultural differences. Recommendations include targeted programming for women Veterans.

Abstract
Introduction: This study utilizes a machine learning model to predict unhealthy alcohol use treatment levels among women of childbearing age. Methods: In this cross-sectional study, women of childbearing age (n = 2397) were screened for alcohol use over a 2-year period as part of the AL-SBIRT (screening, brief intervention, and referral to treatment in Alabama) program in three healthcare settings across Alabama for unhealthy alcohol use severity and depression. A support vector machine learning model was estimated to predict unhealthy alcohol use scores based on depression score and age. Results: The machine learning model was effective in predicting no intervention among patients with lower Patient Health Questionnaire (PHQ)-2 scores of any age, but a brief intervention among younger patients (aged 18–27 years) with PHQ-2 scores &gt;3 and a referral to treatment for unhealthy alcohol use among older patients (between the ages of 25 and 50) with PHQ-2 scores &gt;4. Conclusions: The machine learning model can be an effective tool in predicting unhealthy alcohol use treatment levels and approaches.

Introduction: Mental distress frequently develops in sufferers of chronic diseases, including cancer. We examined the association between physical activity and mental distress among Veteran cancer survivors with heart disease or diabetes. Methods: Data for American military Veteran cancer survivors ( n = 16,643) were retrieved from the Centers for Disease Control and Prevention (CDC) Behavioral Risk Factor Surveillance System (BRFSS). Ordinary least squares (OLS) multiple linear regression was used to explore the effect of physical activity on self-reported mental distress among Veteran cancer survivors with coronary heart disease or diabetes. Geographic information system (GIS) software was used to examine the state-level distribution of mental distress among Veteran cancer survivors. Results: Geographic analysis showed that mental distress (in days) in the last month among Veteran cancer survivors was highest in Alabama (M = 3.99), while those in Wyoming reported the lowest number of days (M = 0.76). After controlling for relevant confounding factors, physical activity was associated with fewer days of mental distress days among Veteran cancer survivors with coronary heart disease. Discussion: Results of this study suggest that physical activity may be beneficial in reducing mental distress among Veteran cancer survivors with heart disease.

Introduction: Little is known about rural–urban disparities in colorectal cancer (CRC) screening rates among the military service member and Veteran (SMV) population in the United States. Given that health care access is a challenge in rural areas, we sought to determine whether rural-dwelling Veterans were less likely to be screened for CRC than urban-dwelling Veterans. Methods: Secondary data for this cross-sectional study were retrieved from the 2016 Behavioral Risk Factor Surveillance System for a national sample of non-institutionalized SMVs ( N = 63,919). The influence of rurality on CRC screening among SMVs was determined using maximum likelihood multiple logistic regression. Results: After controlling for relevant covariates, rurality was independently associated with decreased likelihood of meeting guidelines for CRC screening among SMVs (odds ratio = 0.83, 95% confidence interval, 0.76–0.90). Discussion: Innovative interventions for CRC screening should target SMVs in rural areas because doing so may lower mortality from CRC.

The purpose of this study was to explore the association between psychological resilience and cognitive function in military veterans. We obtained public-use data from the Health and Retirement Study (HRS) for this cross-sectional study of military veterans aged 52 to 101 years (n = 150). We estimated a multivariable linear regression model in which cognitive function served as the dependent variable and psychological resilience served as the independent variable. After controlling for demographics, health conditions, and health behaviors, veterans who had higher psychological resilience scores had better cognitive function (b = 0.22, p = 0.03). Our findings suggest that psychological resilience may be associated with cognitive function among veterans. These findings highlight the importance of assessing psychological resilience in gerontological social work practice.