Rural residence and mental health among US Veterans: Findings from the Millennium Cohort Study

Claire A. Kolaja; Javier Villalobos; Julia Seay; Hope S. McMaster; Edward J. Boyko; Rudolph P. Rull; for the Millennium Cohort Study Team

doi:10.1371/journal.pone.0346780

Abstract

Background

Military veterans are at higher risk of mental health conditions compared to civilians. Some residential characteristics may increase the odds of mental health conditions, but other studies have not examined location attributes (i.e., residential rurality, community social vulnerability, and drive time from Veterans Health Administration [VHA] facilities) and VHA utilization concurrently in association with veteran mental health.

Methods

We analyzed data from 20,423 veterans enrolled in the Millennium Cohort Study, the longest running and largest study of service members and veterans, who completed one pre- and one post-military separation survey (Time 1 and 2, respectively). Time 2 mailing addresses were used to determine location characteristics, including rurality, social vulnerability, and drive time to VHA facilities. VHA enrollment/utilization and mental health outcomes, including probable PTSD, depression, anxiety, and mental quality of life (QOL), were also measured at Time 2. Models adjusting for Time 1 military, demographic and behavioral characteristics were used to examine the association of location characteristics and VHA enrollment/utilization on mental health.

Results

Rurality was not associated with the four mental health outcomes examined. VHA utilization was associated with elevated odds of probable PTSD, depression, anxiety, and lower mental QOL. While community social vulnerability trended toward associations with PTSD and depression, it was only statistically associated with higher odds of anxiety.

Discussion

This study was able to examine residential attributes and VHA utilization on post military mental health. In adjusted models, we found that rurality and drive time to VHA facilities were not associated with mental health. The association between VHA enrollment and utilization with worse mental health was consistent and strong in all models examined.

Citation: Kolaja CA, Villalobos J, Seay J, McMaster HS, Boyko EJ, Rull RP, et al. (2026) Rural residence and mental health among US Veterans: Findings from the Millennium Cohort Study. PLoS One 21(4): e0346780. https://doi.org/10.1371/journal.pone.0346780

Editor: Bettye A. Apenteng, Georgia Southern University, UNITED STATES OF AMERICA

Received: May 13, 2025; Accepted: March 24, 2026; Published: April 17, 2026

This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.

Data Availability: The data are not currently publicly available because of institutional regulations protecting service member survey responses, but they are available on reasonable request and will require data use agreements. Requests for data access may be sent to the Millennium Cohort Study Principal Investigator: usn.point-loma.navhlthrschcensan.mbx.nhrc-millennium-cohort-pi@health.mil.

Funding: The Millennium Cohort Study is funded through the Defense Health Program, U.S. Department of Veterans Affairs Office of Research and Development, U.S. Department of Veterans Affairs HOME (Health Outcomes of Military Exposures), and the U.S. Department of Veterans Affairs Office of Patient Care Services under work unit no. 60002. The funding agency had no part in the study design, collection of the data, analysis of the data, or writing of manuscript. No financials or other conflict of interest were reported by the authors of this paper.

Competing interests: The authors have declared that no competing interests exist.

Introduction

Military veterans are at a higher risk of mental health conditions [1] than the general United States population. The transition from military to civilian life can be a period of intense stress, with challenges from culture shock, interpersonal problems, and employment difficulties potentially increasing this risk [2–4]. The socio-ecological model, which posits that mental health is influenced by a combination of individual attributes and the social and physical environment, provides a robust framework for understanding these dynamics [5]. Within this model, psychological health is shaped by factors across multiple levels—individual, interpersonal, community, and societal—that collectively contribute to both risk and resilience [5].

Prior work suggests that contextual factors may affect mental health as well as individual characteristics like sex, age, or race [6,7]. Environmental features such as green space, walkability, and the presence or absence of physical disorder (e.g., graffiti, traffic) can either mitigate or exasperate stress [8]. In a systematic literature review, certain indicators of neighborhood safety were found to be consistently associated with mental health [9]. Sources of danger can increase feelings of vulnerability while decreasing perceived control, which can result in psychological stress [10,11]. Being the victim or witnessing a crime specifically can increase psychological responses [12]. Areas with high crime rates also have less social cohesion and higher social disorganization [13]. Social isolation can impact feelings of belonging and perceived social support, while sociocultural factors like stoicism and stigma can also vary geographically [14]. Finally, the concentration of healthcare providers in metropolitan areas in the US may hinder access to services and delay treatment for those living elsewhere [15].

To our knowledge, no study examining veteran mental health has explicitly framed their hypotheses using the socio-ecological model, though some have examined related indicators. When examining neighborhood resources and mental health, Park et al. (2021) found that living in alcohol-permissive and tobacco-restrictive communities was associated with psychological distress, while urban/rural residence and access to facilities were not [16]. Another study found that neighborhoods with the lowest socioeconomic status experienced worse mental quality of life [17].

Rurality is one of the most frequently examined contextual factors in veteran mental health literature, often serving as a proxy for individual and community-level sociodemographic factors like lower income and education levels, as well as isolation and fewer resources. However, research examining the mental health of veterans by rurality (e.g., urban versus rural areas) has yielded inconsistent results, often because it fails to account for location attributes. For example, a cross-sectional study of 767,109 VHA-enrolled veterans found that those living in rural areas had worse mental quality of life as determined by the Medical Outcomes Study Short-form 36 (SF-36) Mental Component Summary (MCS) scores than those living in urban settings [18]. Conversely, another study of VHA-enrolled veterans found a higher prevalence of psychiatric disorders among veterans residing in urban areas, yet rural veterans with these disorders experienced worse overall mental health [19]. In contrast, a recent longitudinal analysis of veterans using VHA outpatient services found that those in rural areas reported better overall mental health, although the rural-urban difference decreased over time [20]. Finally, a study examining veterans in the Millennium Cohort Study did not find any differences between those living in rural and urban areas (n = 10,738) [21].

The heterogeneity of these findings may be accounted for by differences in other location attributes. Contextual factors like crime, economic condition, and healthcare access are not randomly distributed and often co-occur. Therefore, it is preferable to use a composite measure that combines several of these factors. Social vulnerability, or the social conditions that affect vulnerability to adverse events such as natural disasters and diseases, may vary widely both between and within urban and rural areas. The U.S. Census created the Social Vulnerability Index (SVI) to measure the susceptibility of communities based on community factors such as poverty, age, transportation, and housing characteristics. Among post-disaster civilian populations, regions with higher SVI scores (indicating more vulnerability) had worse mental and physical health outcomes [22]. Similarly, longer drive times to VHA providers may be an indicator of vulnerability for veterans and reduced access to services. Results from civilian studies regarding the impact of distance to health care facilities on mental health have been mixed [23], which may be due to inconsistencies in study designs and measures of distance. Although the type of rurality (isolated vs micropolitan) and variability in other location attributes may influence veteran mental health, prior studies have not comprehensively examined these factors simultaneously.

Another limitation of prior research examining health differences by urban-rural location is the reliance on overly simplistic definitions of rurality [24]. Most studies have used discrete categories (e.g., urban vs rural) based on population size, density, or commuting patterns. These definitions often fail to differentiate between larger, “micropolitan” rural areas (nonmetropolitan counties with populations between 10,000 and 50,000) and smaller rural areas that are considered “isolated” (defined in the current study by Rural Urban Community Area [RUCA] codes). This distinction may be salient, as some studies have found that individuals living in isolated rural areas may have poorer access to mental healthcare providers as well as higher levels of loneliness than those living in micropolitan rural areas, which may in turn influence mental health outcomes [25,26].

Therefore, there is a clear need to examine the relationship between rurality and mental health among veterans with greater specificity, not only to better understand the potential influence of location on veteran mental health, but also to inform future interventions to address mental health risk and resource allocation among veterans. By not restricting our sample to veterans within the VHA network (i.e., utilizing VHA services), the current study overcame a key limitation of previous research and allowed us to examine whether the influence of residential location on mental health conditions varied by VHA healthcare enrollment as well as by VHA healthcare utilization. Mental health problems (depression, PTSD, anxiety) and mental QOL were compared among veterans enrolled in the Millennium Cohort Study [27] living in isolated rural, micropolitan rural, and urban areas. Our analyses also incorporated social vulnerability and drive time from VHA facilities to clarify the complex associations between residential location and mental health.

Methods

Study population

The current study analyzed data from the Millennium Cohort Study, the largest and longest-running population-based study of service members. A detailed description of the study methods has been published elsewhere [27]. Briefly, participants were enrolled while serving in the military and then surveyed every 3–5 years, both during service and after military separation. The first panel of service members was enrolled in 2001 with additional panels enrolled in 2004, 2007, 2011, and 2020. To date, over 260,000 participants representing all service branches and components are enrolled across these five panels. Participants provided voluntary, informed consent at enrollment on the self-administered web or paper survey and the study protocol was approved by the Naval Health Research Center institutional review board.

In this nested cross-sectional study, Panel 1–4 participants (enrolled between July 1, 2001 and April 4, 2013) were eligible for these analyses if they completed at least one survey while actively serving in the military as active duty, Reserve or National Guard (Time 1) and one survey after separating from the military (Time 2; n = 45,418). Furthermore, as location attributes (i.e., rurality, social vulnerability, and drive time from VHA facilities) were of interest in this study, participants were excluded if their Time 2 location was not in the United States or was not known (n = 12,224). Participants missing Time 2 mental health outcome (n = 5,686), military discharge status (n = 2,049), or Time 1 covariate information (n = 2,582) were excluded from analyses. Further exclusions included completion of the Time 2 survey during the first fiscal year participants were observed in the VHA data (n = 2,454), as exact timing (i.e., before or after Time 2 survey) could not be determined from available annual VHA enrollment and utilization data. This resulted in a final study sample of 20,423 participants.

Measures

Mental health outcomes.

The four mental health outcomes (i.e., PTSD, depression, anxiety, overall mental QOL) were measured at Time 2 (i.e., the first survey completed after separating from the military). PTSD was measured using the 17-item Posttraumatic Stress Disorder Checklist – Civilian Version (PCL-C). PTSD screening criteria were consistent with diagnostic criteria of the Diagnostic and Statistical Manual of Mental Disorders, 4^th Edition, Text Revision (DSM-IV-TR) of endorsing “Moderately” or higher on at least 1 intrusion item, 2 hyper-arousal items, and 3 avoidance items [28–30]. Probable major depressive disorder (MDD) was measured using the 8-item Patient Health Questionnaire (PHQ-8) consistent with the DSM-IV-TR criteria of endorsing at least 5 items as “More than half the days” or higher, in which 1 of the symptoms was anhedonia or depressed mood [31,32]. Symptoms of “panic syndrome” and “other anxiety syndrome” in the previous 4 weeks were assessed using criteria for 2 subscales of the PHQ [33]. “Other anxiety syndrome” was indicated if participants reported “More than half the days” to “Feeling nervous, anxious, on edge, or worrying a lot about different things” and at least 3 of the 6 remaining items on the subscale. Probable “panic syndrome” was indicated if all 4 items about feeling sudden fear/panic were endorsed, as well as to at least 4 of the 11 follow-up symptom items. Subscales were combined so that screening positive for either anxiety or panic syndrome indicated probable anxiety/panic (henceforth referred to as “anxiety”). Finally, overall mental QOL was measured with the mental component score from the Short Form 36 – Health Survey for Veterans (SF-36V), which combines all eight subscales while weighting the mental health scales more heavily. Mental QOL was treated as a continuous outcome, with a mean of 50 and standard deviation of 10, and with higher scores indicating better mental QOL [34].

Health care utilization.

Utilization of VHA through September 2019 was ascertained from a VHA-constructed dataset that provided information by fiscal year regarding participant enrollment and/or utilization of VHA healthcare services. These annual indicators were compared to the Time 2 survey date to categorize participants as 1) not enrolled in the VHA, 2) enrolled but had not utilized VHA care, and 3) enrolled and utilized VHA care by completion of the Time 2 survey.

Residential location characteristics.

Participants’ mailing addresses during Time 2 survey completion were geocoded using the Streetmap Premium extension in ArcGIS Pro (ESRI, 2023) and used to assess three residential location attributes of interest. First, we defined rurality based on the RUCA classification system which was developed by the Washington, Wyoming, Alaska, Montana, Idaho (WWAMI) Rural Health Research Center (RHRC) [35] using population estimates and percent of the community commuting to urban areas. For the current analyses, Categorization B was used to identify veterans residing in urban (RUCA codes 1, 1.1, 2, 2.1, 3, 4.1, 5.1, 7.1, 8.1, 10.1), micropolitan rural (RUCA codes 4, 4.2, 5, 5.2, 6, 6.1), and isolated rural (RUCA codes 7, 7.2, 7.3, 7.4, 8, 8.2, 8.3, 8.4, 9, 9.1, 9.2, 10, 10.2, 10.3, 10.4, 10.5, 10.6) regions. To assess the influence of the operationalization of rurality, we conducted post-hoc analyses replacing discrete RUCA codes with the continuous Index of Relative Rurality (IRR), which combines four indicators: population size, density, remoteness, and built-up area (see supplemental materials for additional details).

Additionally, the residential address of each veteran when they completed their Time 2 survey was assigned a score for social vulnerability using the Centers for Disease Control and Prevention’s (CDC’s) Social Vulnerability Index (SVI). A higher overall percentile ranking for a community indicates relatively more vulnerability based on the four main themes: socioeconomic, household composition/disability, minority status/language, and housing type/transportation [36]. For the purposes of this study, the percentile was standardized with a mean of zero and a standard deviation of one.

Finally, drive time to VHA facilities was determined using Time 2 participant mailing addresses and VHA facilities addresses from the Medicare Wage Index [37]. ArcGIS Pro mapping software was used to identify residences that were more than a 30-minute drive time from the closest VHA healthcare facility. This threshold was chosen to reflect the eligibility requirement from the 2019 VA MISSION Act that expanded access to community healthcare to eligible veterans.

Covariates.

Demographic and military characteristics (age, race, ethnicity, pay grade, service branch, military occupation) were obtained from the Defense Manpower Data Center (DMDC) and if time varying, represent the status as of the Time 1 survey. Type of military discharge condition and date of military separation was also obtained from DMDC and used to represent type of military separation and time between military separation and Time 2 survey completion. Educational attainment and marital status were self-reported on the Time 1 survey and backfilled with DMDC data if self-report information was missing. Enrollment panel was also included as a covariate to account for potential effect measure heterogeneity.

Deployments before the Time 1 survey were identified based on electronic military deployment data in support of operations in Iraq and Afghanistan obtained from DMDC and were combined with combat experience(s) self-reported on the Time 1 survey using 5 items (e.g., “witnessing a person’s death due to war, disaster, or tragic event,” “witnessing instances of physical abuse, such as torture, beating, rape”). DMDC deployment history and combat survey items were used to classify veterans as 1) not deployed, 2) deployed with no combat, or 3) deployed with combat experience [38].

Other covariates, such as problematic drinking, smoking status, sleep duration, physical QOL, mental health status (i.e., probable PTSD, MDD, anxiety and mental QOL), were assessed using Time 1 survey data. Problematic drinking was assessed using the 5-item alcohol abuse and dependence module of the PHQ which assesses symptoms of alcohol misuse over the past 12 months (e.g., “You drove a car after having several drinks or after drinking too much,” “You drank alcohol even though a doctor suggested that you stop drinking because of a problem with your health”). A positive screen for problematic drinking was registered if a yes response was given to one or more items [33]. Smoking status was determined using lifetime report of smoking at least 100 cigarettes and successfully quitting into: never smoker (had not smoked at least 100 cigarettes), former smoker (smoked at least 100 cigarettes and successfully quit) and current smoker (smoked at least 100 cigarettes and had not successfully quit) [39]. Sleep duration was based on a single survey item measuring the average number of hours slept in an average 24-hour period over the past month. Participants who reported 7–9 hours of sleep were considered to sleep the recommended sleep duration [40]. Physical QOL was assessed using the physical component summary score from the Veterans Short Form-36 (SF-36V), with higher scores indicating better overall physical health [34]. Time 1 mental health was assessed using the same methods described above for the outcomes of interest and included as a covariate in the adjusted model for each outcome (e.g., Time 1 probable PTSD was adjusted for in the model Time 2 probable PTSD).

Statistical analysis

Descriptive and bivariate analyses compared residential location rurality with mental health outcomes of interest, VHA health care utilization, other location characteristics, and covariates. Next, to examine the associations between VHA utilization and location characteristics (rurality, social vulnerability, drive time to VHA facilities) with mental health outcomes, logistic regression models were fit to predict probable depression, PTSD, and anxiety, and linear regression models were fit to predict mental QOL. First, unadjusted associations between predictors with mental health outcomes were estimated. Then, models adjusting for panel, age, sex, race, ethnicity, educational attainment, marital status, military characteristics (i.e., pay grade, service branch, military occupation, deployment experience, discharge condition, years since military separation), problem drinking, smoking status, PCS, sleep duration, and Time 1 mental health (PTSD, depression, anxiety, mental QOL) were generated for each outcome. To investigate our secondary aim of determining whether relationships differ between rurality by health care utilization, an interaction term for rurality and VHA care utilization was included in each fully adjusted model. Multicollinearity was assessed using the variance inflation factor, in which a value of 4 or greater indicated possible collinearity. All analyses were conducted using SAS/STAT software, version 9.4.

Results

Descriptive results

Among the 20,423 veterans eligible for these analyses, 88.3% lived in an urban location, 7.6% lived in a micropolitan rural location, and 4.1% lived in an isolated rural location at Time 2 (Table 1). Overall, Time 2 prevalence of probable PTSD was 16.8%, depression was 11.4%, anxiety was 13.4%, and the average mental QOL was 47.2 (standard deviation [SD]: 12.8). More than half (52.0%) of participants had enrolled in and utilized VHA care before the Time 2 survey, while 5.2% enrolled but did not utilize VHA care, and 42.7% had not contacted the VHA before the Time 2 survey.

Download:

Table 1. Characteristics of mental health outcomes and predictors of interest by rurality± among Veteran Millennium Cohort Study participants.

https://doi.org/10.1371/journal.pone.0346780.t001

The average age of participants at Time 1 was 31.5 years (SD: 8.8 years) and a majority were male (69.1%) and non-Hispanic White (75.3%). At Time 1, the most common characteristics were some college experience but had not obtained a degree (42.4%), married (58.3%), junior enlisted pay grade (44.0%), serving in the Army (38.4%), had not deployed (47.5%), and worked in other occupations (e.g., electrical or mechanical equipment repair, craft workers; 44.7%). At separation, most were discharged honorably (75.3%) with an average of 3.1 years (SD: 2.1) between separation from the military and the completion of the Time 2 survey. Most participants did not screen positive for problem drinking (87.1%), never smoked cigarettes (54.8%), did not screen positive for depression, PTSD, and anxiety (93.2%, 90.4%, 92.7%, respectively), and slept between 7 and 9 hours (62.2%). Average physical QOL of 51.4 (SD: 9.0) and mental QOL of 49.3 (SD: 11.0) were observed at Time 1.

Bivariate associations

At the bivariate level, rurality was associated with probable PTSD and not associated with depression, anxiety, or mental QOL (Table 2). That is, compared to veterans in urban locations, those in micropolitan rural or isolated rural locations had higher odds of PTSD (micropolitan odds ratios [OR], 95% confidence interval [95% CI]: 1.16, 1.01–1.32 and isolated OR, 95% CI: 1.21, 1.02–1.45). VHA utilization was associated with all mental health outcomes, such that, compared to those not enrolled in the VHA by Time 2, veterans who had enrolled and not utilized care were more likely to screen positive for PTSD (OR, 95% CI: 1.42, 1.15–1.75), depression (OR, 95% CI: 1.34, 1.03–1.73), anxiety (OR, 95% CI: 1.55, 1.23–1.95) and report lower mental QOL (mean difference −1.02, standard error [SE]: 0.40). Furthermore, the association for veterans who enrolled and utilized VHA care was even stronger; they were more likely to screen positive for PTSD (OR 3.99, 95% CI: 3.65–4.37), depression (OR 3.83, 95% CI: 3.44–4.26), anxiety (OR 4.05, 95% CI: 3.66–4.48), and report lower mental QOL (mean difference −6.14, SE: 0.18). Social vulnerability was also associated with all four mental health outcomes; a one standard deviation increment in community social vulnerability (SVI) was associated with greater odds of screening positive for PTSD (OR 1.22, 95% CI: 1.18–1.27), depression (OR 1.21, 95% CI: 1.16–1.27), anxiety (OR 1.20, 95% CI: 1.15–1.25), and lower mental QOL (mean difference −1.11, SE: 0.09). Longer drive times to VHA facilities was not associated with any of the outcomes.

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Table 2. Regression models examining relationship between rurality, health care utilization, and other location attributes on mental health among Veteran Millennium Cohort Study participants (n = 20,423).

https://doi.org/10.1371/journal.pone.0346780.t002

Adjusted associations

In the adjusted models (Table 2), rurality did not appear to be associated with the mental health outcomes of interest. VHA utilization was significantly associated with all outcomes; veterans who enrolled and utilized VHA care by Time 2 showed a greater than twofold difference in screening positive for PTSD (adjusted odds ratio; AOR 2.61, 95% CI: 2.35–2.90), depression (AOR 2.56, 95% CI: 2.26–2.88), and anxiety (AOR 2.66, 95% CI: 2.38–2.98), and reported lower mental QOL (adjusted mean difference −3.01, SE: 0.17) compared to veterans not enrolled. Greater community social vulnerability was significantly associated with higher odds of anxiety (AOR 1.06, 95% CI: 1.01–1.11), while positive associations between community social vulnerability with PTSD and depression trended towards significance. Drive time to VHA facilities was not associated with any of the mental health outcomes. Finally, we investigated if mental health varied by rurality and VHA utilization by including the interaction between rurality and VHA utilization in the adjusted model for each outcome; interactions did not meet the specified statistical significance threshold (p-value > .05). Associations for the covariates included in the adjusted models in Table 2 and mental health outcomes are displayed in S1 Table.

Supplemental analyses

See supplemental material for results from the post-hoc analyses conducted utilizing a continuous measure of rurality (Index of Relative Rurality [IRR]). In brief, bivariate and adjusted association between continuous rurality and the mental health outcomes examined aligned with those reported for the main analyses. One notable difference was found for the mental QOL in the fully adjusted model; IRR was significantly associated with mental QOL (p-value = 0.03) such that for a one unit increase in IRR, mental QOL was 1.54 units higher (S2 Table).

Discussion

The World Health Organization (WHO) emphasizes that mental health is shaped not only by individual attributes but also by the social circumstances and environment in which individuals live [41]. This perspective is rooted in the socio-ecological model, which is broadly used to conceptualize psychological health and to identify factors at different levels (individual, interpersonal, community, and society) that may contribute to risk and resiliency [5]. Although several studies have examined associations between rurality and veteran health, to our knowledge, no studies have concurrently examined additional community attributes, such as social vulnerability, and drive time to VHA facilities, alongside VHA utilization, in a sample that includes both VHA-enrolled and non VHA-enrolled veterans. This study aimed to examine the relationship between residential location and veteran mental health using the broad socio-ecological framework to help disentangle the conflicting findings reported in previous studies. Final analyses indicated that veterans enrolled in and utilizing VHA care were more likely to screen positive for mental health conditions. Rurality was associated only with mental QOL, where micropolitan rural and isolated rural veterans reported modestly higher mental QOL compared with those in urban areas. Longer drive time to VHA facilities was not associated with post-military separation mental health.

Previous literature on rurality and veteran mental health reported inconsistent findings [18,20,21,42,43] that may be artifacts of heterogeneous definitions of rurality and mental health outcomes examined, the specific geographic location (e.g., a single state), examined older data, or focused on veterans enrolled in or utilizing VHA care. Descriptive results from the current study revealed that compared to urban counterparts, veterans living in isolated locations were more likely to be younger, less educated, junior enlisted pay grade at Time 1, experienced a deployment with combat, and discharged from the military with general or bad, dishonorable, or other than honorable status. Many of these are known risk factors for mental health conditions [44], which may explain why, when compared to veterans living in urban areas, veterans living in isolated rural locations were more likely to have PTSD in bivariate analyses, but no association between rurality and PTSD was observed in the adjusted model. While prior research has theorized that heightened isolation or a lack of resources in rural areas may negatively impact health [16,19,42,43,45–49], certain veterans who select rural residence may prefer various aspects of rural residence (e.g., privacy, peace, and quiet) [50] that may support and improve mental health. One notable finding from the adjusted models supportive of this theory was that veterans living in rural locations had modestly higher (better) mental QOL. This association reached statistical significance in the supplemental analyses using the continuous rurality measure. To our knowledge, no other study on veteran mental health has utilized a continuous measure of rurality although prior work conducted among civilians has compared continuous and categorical measures and highlighted similar findings (e.g., that the statistical significance mostly remained consistent regardless of rurality measure used) [51].

Regardless of how it is operationalized, rurality is a proxy for more specific location-based attributes. To investigate the socio-ecological model more directly, this study included additional community characteristics, such as social vulnerability and drive time to VHA facilities. While the associations between social vulnerability with PTSD, depression and mental QOL (p-values = 0.08–0.09) did not reach statistical significance, this marginal trend may suggest that living in more socially vulnerable areas has an adverse impact on mental health. This interpretation aligns with civilian studies reporting relationships between greater social vulnerability and worse mental health outcomes [22,52], potentially due to factors like fewer community resources [16] and heightened safety concerns [53]. Our nuanced findings are consistent with the broader literature. Prior meta-analyses and systematic reviews also reported heterogenous results when linking neighborhood factors to individual mental health [54,55]. This underscores that the detected relationships are often sensitive to the specific sample and methods used, highlighting the complexity of the socio-ecological model.

Furthermore, we found that residing more than a 30-minute drive from VHA healthcare facilities was not associated with mental health outcomes. While previous studies of veterans utilizing VHA care identified distance as a primary barrier to healthcare access [56,57], our finding aligns with contemporary research and may reflect a new reality in veteran healthcare [16]. The expansion of healthcare coverage for veterans through the CHOICE Act of 2014 and the VHA’s significant investment in telehealth infrastructure [44,45] may have fundamentally changed how veterans access services, potentially mitigating the historical impact of geographic distance [46–48].

In the fully adjusted models, we consistently found a positive association between utilization of VHA for healthcare with screening positive for mental health conditions. This finding aligns with several other studies that similarly found that VHA utilizers report worse mental health than veterans not utilizing VHA care [58–62]. This is not surprising as eligibility for VHA enrollment and prioritization of enrollment is based on service-related factors and income criteria [63], which skews the enrolled population to patients with higher health care needs. These findings align with the integration of mental health care in VHA primary care, resulting in more patients being screened and treated. These programs emphasize early detection and intervention of mental health symptoms. Prior work found that over 60% of veterans who screen positive for PTSD in a primary care setting engage with mental health treatment afterward (e.g., referral to a mental health clinic) [64]. The VHA may benefit from future research on barriers (contextual and individual-level) that hinder mental healthcare receipt among veterans.

The limitations of the current study should be considered when interpreting the findings described above. The present study leveraged self-reported data using mental health screeners, and therefore findings regarding mental health outcomes do not specifically refer to clinical diagnoses. As almost half of participants did not utilize the VHA for healthcare (42.7% were not enrolled and 5.2% were enrolled but did not utilize care), it was not feasible to incorporate clinical diagnosis of mental health conditions in this study. Actual diagnosis at the VHA by rurality is a separate analytic question and warrants future study. The study was also missing information on healthcare received outside of the VHA. Outcomes were reported between 2004–2016 and could have been influenced by external factors, such as global and economic events, that may not be accounted for in these models. The rurality categorization used in this study differed from the classification utilized by the VHA Office of Rural Health (ORH), which may limit the ability to compare findings. The classification used by the VA ORH categorizes even fewer veterans in isolated areas, however, post-hoc analyses revealed that using this categorization did not change the reported findings (screening positive for PTSD p = 0.50, major depression p = 0.74, and anxiety/panic p = 0.92, and MCS p = 0.08). In addition, as mailing addresses were used to determine rurality, there is a chance that residence could be different for some participants. We were not able to examine the full spectrum of individual (e.g., birth and childhood location, number of moves) and built environment factors that may vary by rurality that could affect mental health, such as available green space, noise from road traffic, and pollution. Finally, the Millennium Cohort Study enrolled service members beginning in July of 2001. Therefore, the results we report may not apply to veterans prior to this time.

This study has multiple notable strengths. The Millennium Cohort Study is the largest and longest running cohort study of service members and designed to follow participants after military separation through follow-up surveys and VHA records. Mailing addresses were merged with location specific factors (rurality, social vulnerability, drive time to VHA facilities) so that these factors could be explored concurrently in adjusted models. Finally, we were able to examine all veterans enrolled in the Millennium Cohort Study and not restricted to those utilizing VHA care.

In conclusion, this study explored associations between post-military location attributes and VHA utilization with veteran mental health while controlling for pre-separation characteristics among a relatively young sample of post 9/11 veterans within a few years of separation. Rurality and drive time to VHA facilities were not associated with mental health conditions after adjustment for pertinent covariates. Instead, VHA enrollment and utilization were consistently associated with worse mental health. These findings highlight the association between VHA enrollment and utilization with mental health symptoms and may contribute to VHA understanding of veterans with higher mental health needs as well as resource allocation.

Supporting information

S1 Table. Associations between risk and protective factors with Time 2 mental health outcomes among Veteran Millennium Cohort Study participants as included in adjusted models in Table 2, n = 20,423.

https://doi.org/10.1371/journal.pone.0346780.s001

(DOCX)

S2 Table. Associations between continuous rurality and mental health outcomes, n = 20,418.

https://doi.org/10.1371/journal.pone.0346780.s002

(DOCX)

Acknowledgments

In addition to the authors, the Millennium Cohort Study team includes Anna Baccetti, MPH; Satbir K. Boparai, MBA; Felicia R. Carey, PhD; Sheila F. Castaneda, PhD; Toni Rose Geronimo-Hara, MPH; Judith Harbertson, PhD, MPH; Yohannes Haile, MS; Isabel G. Jacobson, MPH; Cynthia A. LeardMann, MPH; Erin L. Richard PhD, MPH; Anna C. Rivera, MPH; Beverly D. Sheppard; Karen Tannenbaum, PhD, MA; Daniel W. Trone, PhD; Jennifer L. Walstrom; Kerris J. Woods; Katie Zhu, MPH. The authors also appreciate contributions from Leidos, Inc. We greatly appreciate the contributions of the Millennium Cohort Study participants.

References

1. Schein J, Houle C, Urganus A, Cloutier M, Patterson-Lomba O, Wang Y, et al. Prevalence of post-traumatic stress disorder in the United States: A systematic literature review. Curr Med Res Opin. 2021;37(12):2151–61. pmid:34498953
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- PubMed/NCBI
- Google Scholar
2. Taylor S, Miller BL, Tallapragada M, Vogel M. Veterans’ transition out of the military and knowledge of mental health disorders. 2020.
3. Pease JL, Billera M, Gerard G. Military culture and the transition to civilian life: Suicide risk and other considerations. Soc Work. 2016;61(1):83–6. pmid:26898003
- View Article
- PubMed/NCBI
- Google Scholar
4. Mobbs MC, Bonanno GA. Beyond war and PTSD: The crucial role of transition stress in the lives of military veterans. Clin Psychol Rev. 2018;59:137–44. pmid:29180101
- View Article
- PubMed/NCBI
- Google Scholar
5. Reupert A. A socio-ecological framework for mental health and well-being. Taylor & Francis. 2017.
6. Oakes JM, Andrade KE, Biyoow IM, Cowan LT. Twenty Years of Neighborhood Effect Research: An Assessment. Curr Epidemiol Rep. 2015;2(1):80–7. pmid:28133588
- View Article
- PubMed/NCBI
- Google Scholar
7. Lakhan R, Ekúndayò O. Application of the ecological framework in depression: An approach whose time has come. Arch Ment Health. 2013;14(2):103.
- View Article
- Google Scholar
8. Gong Y, Palmer S, Gallacher J, Marsden T, Fone D. A systematic review of the relationship between objective measurements of the urban environment and psychological distress. Environ Int. 2016;96:48–57. pmid:27599349
- View Article
- PubMed/NCBI
- Google Scholar
9. Won J, Lee C, Forjuoh SN, Ory MG. Neighborhood safety factors associated with older adults’ health-related outcomes: A systematic literature review. Soc Sci Med. 2016;165:177–86. pmid:27484353
- View Article
- PubMed/NCBI
- Google Scholar
10. De Donder L, Buffel T, Dury S, De Witte N, Verté D. Perceptual quality of neighbourhood design and feelings of unsafety. Ageing and Society. 2012;33(6):917–37.
- View Article
- Google Scholar
11. Downey L, Van Willigen M. Environmental stressors: The mental health impacts of living near industrial activity. J Health Soc Behav. 2005;46(3):289–305. pmid:16259150
- View Article
- PubMed/NCBI
- Google Scholar
12. Baranyi G, Di Marco MH, Russ TC, Dibben C, Pearce J. The impact of neighbourhood crime on mental health: A systematic review and meta-analysis. Soc Sci Med. 2021;282:114106. pmid:34139480
- View Article
- PubMed/NCBI
- Google Scholar
13. Kingsbury M, Clayborne Z, Colman I, Kirkbride JB. The protective effect of neighbourhood social cohesion on adolescent mental health following stressful life events. Psychol Med. 2020;50(8):1292–9. pmid:31179962
- View Article
- PubMed/NCBI
- Google Scholar
14. Hirsch JK, Cukrowicz KC. Suicide in rural areas: An updated review of the literature. Journal of Rural Mental Health. 2014;38(2):65–78.
- View Article
- Google Scholar
15. Probst J, Eberth JM, Crouch E. Structural urbanism contributes to poorer health outcomes for rural America. Health Aff (Millwood). 2019;38(12):1976–84. pmid:31794301
- View Article
- PubMed/NCBI
- Google Scholar
16. Shin Park Y, Wyman JF, McMorris BJ, Pruinelli L, Song Y, Kaas MJ, et al. Evaluation of neighborhood resources and mental health in American military Veterans using geographic information systems. Prev Med Rep. 2021;24:101546. pmid:34976617
- View Article
- PubMed/NCBI
- Google Scholar
17. Nelson K, Taylor L, Lurie N, Escarce J, McFarland L, Fihn SD. Neighborhood environment and health status and mortality among veterans. J Gen Intern Med. 2011;26(8):862–7. pmid:21499826
- View Article
- PubMed/NCBI
- Google Scholar
18. Weeks WB, Kazis LE, Shen Y, Cong Z, Ren XS, Miller D, et al. Differences in health-related quality of life in rural and urban veterans. Am J Public Health. 2004;94(10):1762–7. pmid:15451747
- View Article
- PubMed/NCBI
- Google Scholar
19. Wallace AE, Weeks WB, Wang S, Lee AF, Kazis LE. Rural and urban disparities in health-related quality of life among veterans with psychiatric disorders. Psychiatr Serv. 2006;57(6):851–6. pmid:16754763
- View Article
- PubMed/NCBI
- Google Scholar
20. Wallace AE, Lee R, Mackenzie TA, West AN, Wright S, Booth BM, et al. A longitudinal analysis of rural and urban veterans’ health-related quality of life. J Rural Health. 2010;26(2):156–63. pmid:20447002
- View Article
- PubMed/NCBI
- Google Scholar
21. Proctor SP, Wells TS, Jones KA, Boyco EJ, Smith TC. Examination of post-service health-related quality of life among rural and urban military members of the Millennium Cohort Study. Journal of Rural Social Sciences. 2011;26(3):3.
- View Article
- Google Scholar
22. Hahn MB, Van Wyck R, Lessard L, Fried R. Compounding effects of social vulnerability and recurring natural disasters on mental and physical health. Disaster Med Public Health Prep. 2022;16(3):1013–21. pmid:33757617
- View Article
- PubMed/NCBI
- Google Scholar
23. LaVela SL, Smith B, Weaver FM, Miskevics SA. Geographical proximity and health care utilization in veterans with SCI&D in the USA. Soc Sci Med. 2004;59(11):2387–99. pmid:15450711
- View Article
- PubMed/NCBI
- Google Scholar
24. Long JC, Delamater PL, Holmes GM. Which Definition of Rurality Should I Use?: The relative performance of 8 federal rural definitions in identifying rural-urban disparities. Med Care. 2021;59(Suppl 5):S413–9. pmid:34524237
- View Article
- PubMed/NCBI
- Google Scholar
25. Andrilla CHA, Coulthard C, Patterson DG. Prescribing practices of rural physicians waivered to prescribe buprenorphine. Am J Prev Med. 2018;54(6 Suppl 3):S208–14. pmid:29779544
- View Article
- PubMed/NCBI
- Google Scholar
26. Henning-Smith C, Wu Z, Lahr M. Unmet need for personal care assistance among rural and urban older adults. University of Minnesota. 2019.
- View Article
- Google Scholar
27. Castañeda SF, Belding JN, Kolaja CA, LeardMann CA, Jacobson IG, Rivera AC, et al. Cohort profile update: The US Millennium Cohort Study-evaluating the impact of military experiences on service members and veteran health. Int J Epidemiol. 2023;52(4):e222–31. pmid:37348866
- View Article
- PubMed/NCBI
- Google Scholar
28. Weathers FW, Litz BT, Herman DS, Huska JA, Keane TM. The PTSD Checklist (PCL): Reliability, validity, and diagnostic utility. San Antonio, TX, 1993.
- View Article
- Google Scholar
29. Bliese PD, Wright KM, Adler AB, Cabrera O, Castro CA, Hoge CW. Validating the primary care posttraumatic stress disorder screen and the posttraumatic stress disorder checklist with soldiers returning from combat. J Consult Clin Psychol. 2008;76(2):272–81. pmid:18377123
- View Article
- PubMed/NCBI
- Google Scholar
30. Blanchard EB, Jones-Alexander J, Buckley TC, Forneris CA. Psychometric properties of the PTSD Checklist (PCL). Behav Res Ther. 1996;34(8):669–73. pmid:8870294
- View Article
- PubMed/NCBI
- Google Scholar
31. Kroenke K, Strine TW, Spitzer RL, Williams JBW, Berry JT, Mokdad AH. The PHQ-8 as a measure of current depression in the general population. J Affect Disord. 2009;114(1–3):163–73. pmid:18752852
- View Article
- PubMed/NCBI
- Google Scholar
32. Kroenke K, Spitzer RL, Williams JBW, Löwe B. The patient health questionnaire somatic, anxiety, and depressive symptom scales: A systematic review. Gen Hosp Psychiatry. 2010;32(4):345–59. pmid:20633738
- View Article
- PubMed/NCBI
- Google Scholar
33. Spitzer RL, Kroenke K, Williams JB, Group PHQPCS, Group PHQPCS. Validation and utility of a self-report version of PRIME-MD: The PHQ primary care study. JAMA. 1999;282(18):1737–44.
- View Article
- Google Scholar
34. Ware JE, Gandek B, Kosinski M, Aaronson NK, Apolone G, Brazier J, et al. The equivalence of SF-36 summary health scores estimated using standard and country-specific algorithms in 10 countries: Results from the IQOLA Project. International Quality of Life Assessment. J Clin Epidemiol. 1998;51(11):1167–70. pmid:9817134
- View Article
- PubMed/NCBI
- Google Scholar
35. WWAMI Rural Health Research Center. RUCA data: using RUCA data 2010.http://depts.washington.edu/uwruca/ruca-uses.php
36. CDC/ATSDR Social Vulnerability Index. https://www.atsdr.cdc.gov/placeandhealth/svi/data_documentation_download.html. 2020.
37. HERC’s Medicare Wage Index for VA Facilities. https://www.herc.research.va.gov/include/page.asp?id=guidebook-wage-index. 2023.
38. Porter B, Hoge CW, Tobin LE, Donoho CJ, Castro CA, Luxton DD, et al. Measuring aggregated and specific combat exposures: Associations between combat exposure measures and posttraumatic stress disorder, depression, and alcohol-related problems. J Trauma Stress. 2018;31(2):296–306. pmid:29603393
- View Article
- PubMed/NCBI
- Google Scholar
39. National Center for Health Statistics. Health, United States, 2019. 2021.
40. Jacobson IG, Horton JL, Smith B, Wells TS, Boyko EJ, Lieberman HR, et al. Bodybuilding, energy, and weight-loss supplements are associated with deployment and physical activity in U.S. military personnel. Ann Epidemiol. 2012;22(5):318–30. pmid:22445519
- View Article
- PubMed/NCBI
- Google Scholar
41. Organization WH. WHOQOL user manual. Division of mental health and prevention of substance abuse. World Health Organization. 2013.
42. Boscarino JJ, Figley CR, Adams RE, Urosevich TG, Kirchner HL, Boscarino JA. Mental health status in veterans residing in rural versus non-rural areas: Results from the veterans’ health study. Mil Med Res. 2020;7(1):44. pmid:32951600
- View Article
- PubMed/NCBI
- Google Scholar
43. Breslau J, Marshall GN, Pincus HA, Brown RA. Are mental disorders more common in urban than rural areas of the United States?. J Psychiatr Res. 2014;56:50–5. pmid:24857610
- View Article
- PubMed/NCBI
- Google Scholar
44. Ramchand R, Rudavsky R, Grant S, Tanielian T, Jaycox L. Prevalence of, risk factors for, and consequences of posttraumatic stress disorder and other mental health problems in military populations deployed to Iraq and Afghanistan. Curr Psychiatry Rep. 2015;17(5):37. pmid:25876141
- View Article
- PubMed/NCBI
- Google Scholar
45. Cully JA, Jameson JP, Phillips LL, Kunik ME, Fortney JC. Use of psychotherapy by rural and urban veterans. J Rural Health. 2010;26(3):225–33. pmid:20633090
- View Article
- PubMed/NCBI
- Google Scholar
46. Fischer EP, McCarthy JF, Ignacio RV, Blow FC, Barry KL, Hudson TJ, et al. Longitudinal patterns of health system retention among veterans with schizophrenia or bipolar disorder. Community Ment Health J. 2008;44(5):321–30. pmid:18401711
- View Article
- PubMed/NCBI
- Google Scholar
47. Hudson TJ, Fortney JC, Williams JS, Austen MA, Pope SK, Hayes CJ. Effect of rural residence on use of VHA mental health care among OEF/OIF veterans. Psychiatr Serv. 2014;65(12):1420–5. pmid:25081581
- View Article
- PubMed/NCBI
- Google Scholar
48. Spoont M, Greer N, Su J, Fitzgerald P, Rutks I, Wilt T. Rural vs. urban ambulatory health care: A systematic review. 2011.
49. Teich J, Ali MM, Lynch S, Mutter R. Utilization of mental health services by veterans living in rural areas. J Rural Health. 2017;33(3):297–304. pmid:27701791
- View Article
- PubMed/NCBI
- Google Scholar
50. Jansen SJT. Urban, suburban or rural? Understanding preferences for the residential environment. Journal of Urbanism: International Research on Placemaking and Urban Sustainability. 2020;13(2):213–35.
- View Article
- Google Scholar
51. Franks JA, Davis ES, Bhatia S, Kenzik KM. Defining rurality: An evaluation of rural definitions and the impact on survival estimates. J Natl Cancer Inst. 2023;115(5):530–8. pmid:36762829
- View Article
- PubMed/NCBI
- Google Scholar
52. Yoo E-H, Roberts JE, Eum Y, Li X, Konty K. Exposure to urban green space may both promote and harm mental health in socially vulnerable neighborhoods: A neighborhood-scale analysis in New York City. Environ Res. 2022;204(Pt C):112292. pmid:34728238
- View Article
- PubMed/NCBI
- Google Scholar
53. Meyer OL, Castro-Schilo L, Aguilar-Gaxiola S. Determinants of mental health and self-rated health: A model of socioeconomic status, neighborhood safety, and physical activity. Am J Public Health. 2014;104(9):1734–41. pmid:25033151
- View Article
- PubMed/NCBI
- Google Scholar
54. Moore THM, Kesten JM, López-López JA, Ijaz S, McAleenan A, Richards A, et al. The effects of changes to the built environment on the mental health and well-being of adults: Systematic review. Health Place. 2018;53:237–57. pmid:30196042
- View Article
- PubMed/NCBI
- Google Scholar
55. Richardson R, Westley T, Gariépy G, Austin N, Nandi A. Neighborhood socioeconomic conditions and depression: A systematic review and meta-analysis. Soc Psychiatry Psychiatr Epidemiol. 2015;50(11):1641–56. pmid:26164028
- View Article
- PubMed/NCBI
- Google Scholar
56. Buzza C, Ono SS, Turvey C, Wittrock S, Noble M, Reddy G, et al. Distance is relative: Unpacking a principal barrier in rural healthcare. J Gen Intern Med. 2011;26 Suppl 2(Suppl 2):648–54. pmid:21989617
- View Article
- PubMed/NCBI
- Google Scholar
57. Goins RT, Williams KA, Carter MW, Spencer M, Solovieva T. Perceived barriers to health care access among rural older adults: A qualitative study. J Rural Health. 2005;21(3):206–13. pmid:16092293
- View Article
- PubMed/NCBI
- Google Scholar
58. Fink DS, Stohl M, Mannes ZL, Shmulewitz D, Wall M, Gutkind S, et al. Comparing mental and physical health of U.S. veterans by VA healthcare use: implications for generalizability of research in the VA electronic health records. BMC Health Serv Res. 2022;22(1):1500. pmid:36494829
- View Article
- PubMed/NCBI
- Google Scholar
59. Meffert BN, Morabito DM, Sawicki DA, Hausman C, Southwick SM, Pietrzak RH. US veterans who do and do not utilize veterans affairs health care services: demographic, military, medical, and psychosocial characteristics. The Primary Care Companion for CNS Disorders. 2019;21(1):26992.
- View Article
- Google Scholar
60. Nelson KM, Starkebaum GA, Reiber GE. Veterans using and uninsured veterans not using Veterans Affairs (VA) health care. Public Health Rep. 2007;122(1):93–100. pmid:17236614
- View Article
- PubMed/NCBI
- Google Scholar
61. Porter B, Dozier ME, Seelig AD, Zhu Y, Patoilo MS, Boyko EJ, et al. Posttraumatic stress disorder, Veterans Health Administration use, and care-seeking among recent-era U.S. veterans. J Trauma Stress. 2024;37(3):460–70. pmid:38424733
- View Article
- PubMed/NCBI
- Google Scholar
62. Sayer NA, Orazem RJ, Noorbaloochi S, Gravely A, Frazier P, Carlson KF, et al. Iraq and afghanistan war veterans with reintegration problems: Differences by veterans affairs healthcare user status. Adm Policy Ment Health. 2015;42(4):493–503. pmid:24913102
- View Article
- PubMed/NCBI
- Google Scholar
63. Maynard C, Nelson K. Compensation for veterans with service connected disabilities: Current findings and future implications. Journal of Disability Policy Studies. 2020;31(1):57–62.
- View Article
- Google Scholar
64. Bovin MJ, Resnik J, Linsky AM, Stolzmann K, Mull HJ, Schnurr PP, et al. Does screening for PTSD lead to VA mental health care? Identifying the spectrum of initial VA screening actions. Psychol Serv. 2023;20(3):525–32. pmid:35446094
- View Article
- PubMed/NCBI
- Google Scholar

[ref1] 1. Schein J, Houle C, Urganus A, Cloutier M, Patterson-Lomba O, Wang Y, et al. Prevalence of post-traumatic stress disorder in the United States: A systematic literature review. Curr Med Res Opin. 2021;37(12):2151–61. pmid:34498953
View Article
PubMed/NCBI
Google Scholar

[2] View Article

[3] PubMed/NCBI

[4] Google Scholar

[ref2] 2. Taylor S, Miller BL, Tallapragada M, Vogel M. Veterans’ transition out of the military and knowledge of mental health disorders. 2020.

[ref3] 3. Pease JL, Billera M, Gerard G. Military culture and the transition to civilian life: Suicide risk and other considerations. Soc Work. 2016;61(1):83–6. pmid:26898003
View Article
PubMed/NCBI
Google Scholar

[7] View Article

[8] PubMed/NCBI

[9] Google Scholar

[ref4] 4. Mobbs MC, Bonanno GA. Beyond war and PTSD: The crucial role of transition stress in the lives of military veterans. Clin Psychol Rev. 2018;59:137–44. pmid:29180101
View Article
PubMed/NCBI
Google Scholar

[11] View Article

[12] PubMed/NCBI

[13] Google Scholar

[ref5] 5. Reupert A. A socio-ecological framework for mental health and well-being. Taylor & Francis. 2017.

[ref6] 6. Oakes JM, Andrade KE, Biyoow IM, Cowan LT. Twenty Years of Neighborhood Effect Research: An Assessment. Curr Epidemiol Rep. 2015;2(1):80–7. pmid:28133588
View Article
PubMed/NCBI
Google Scholar

[16] View Article

[17] PubMed/NCBI

[18] Google Scholar

[ref7] 7. Lakhan R, Ekúndayò O. Application of the ecological framework in depression: An approach whose time has come. Arch Ment Health. 2013;14(2):103.
View Article
Google Scholar

[20] View Article

[21] Google Scholar

[ref8] 8. Gong Y, Palmer S, Gallacher J, Marsden T, Fone D. A systematic review of the relationship between objective measurements of the urban environment and psychological distress. Environ Int. 2016;96:48–57. pmid:27599349
View Article
PubMed/NCBI
Google Scholar

[23] View Article

[24] PubMed/NCBI

[25] Google Scholar

[ref9] 9. Won J, Lee C, Forjuoh SN, Ory MG. Neighborhood safety factors associated with older adults’ health-related outcomes: A systematic literature review. Soc Sci Med. 2016;165:177–86. pmid:27484353
View Article
PubMed/NCBI
Google Scholar

[27] View Article

[28] PubMed/NCBI

[29] Google Scholar

[ref10] 10. De Donder L, Buffel T, Dury S, De Witte N, Verté D. Perceptual quality of neighbourhood design and feelings of unsafety. Ageing and Society. 2012;33(6):917–37.
View Article
Google Scholar

[31] View Article

[32] Google Scholar

[ref11] 11. Downey L, Van Willigen M. Environmental stressors: The mental health impacts of living near industrial activity. J Health Soc Behav. 2005;46(3):289–305. pmid:16259150
View Article
PubMed/NCBI
Google Scholar

[34] View Article

[35] PubMed/NCBI

[36] Google Scholar

[ref12] 12. Baranyi G, Di Marco MH, Russ TC, Dibben C, Pearce J. The impact of neighbourhood crime on mental health: A systematic review and meta-analysis. Soc Sci Med. 2021;282:114106. pmid:34139480
View Article
PubMed/NCBI
Google Scholar

[38] View Article

[39] PubMed/NCBI

[40] Google Scholar

[ref13] 13. Kingsbury M, Clayborne Z, Colman I, Kirkbride JB. The protective effect of neighbourhood social cohesion on adolescent mental health following stressful life events. Psychol Med. 2020;50(8):1292–9. pmid:31179962
View Article
PubMed/NCBI
Google Scholar

[42] View Article

[43] PubMed/NCBI

[44] Google Scholar

[ref14] 14. Hirsch JK, Cukrowicz KC. Suicide in rural areas: An updated review of the literature. Journal of Rural Mental Health. 2014;38(2):65–78.
View Article
Google Scholar

[46] View Article

[47] Google Scholar

[ref15] 15. Probst J, Eberth JM, Crouch E. Structural urbanism contributes to poorer health outcomes for rural America. Health Aff (Millwood). 2019;38(12):1976–84. pmid:31794301
View Article
PubMed/NCBI
Google Scholar

[49] View Article

[50] PubMed/NCBI

[51] Google Scholar

[ref16] 16. Shin Park Y, Wyman JF, McMorris BJ, Pruinelli L, Song Y, Kaas MJ, et al. Evaluation of neighborhood resources and mental health in American military Veterans using geographic information systems. Prev Med Rep. 2021;24:101546. pmid:34976617
View Article
PubMed/NCBI
Google Scholar

[53] View Article

[54] PubMed/NCBI

[55] Google Scholar

[ref17] 17. Nelson K, Taylor L, Lurie N, Escarce J, McFarland L, Fihn SD. Neighborhood environment and health status and mortality among veterans. J Gen Intern Med. 2011;26(8):862–7. pmid:21499826
View Article
PubMed/NCBI
Google Scholar

[57] View Article

[58] PubMed/NCBI

[59] Google Scholar

[ref18] 18. Weeks WB, Kazis LE, Shen Y, Cong Z, Ren XS, Miller D, et al. Differences in health-related quality of life in rural and urban veterans. Am J Public Health. 2004;94(10):1762–7. pmid:15451747
View Article
PubMed/NCBI
Google Scholar

[61] View Article

[62] PubMed/NCBI

[63] Google Scholar

[ref19] 19. Wallace AE, Weeks WB, Wang S, Lee AF, Kazis LE. Rural and urban disparities in health-related quality of life among veterans with psychiatric disorders. Psychiatr Serv. 2006;57(6):851–6. pmid:16754763
View Article
PubMed/NCBI
Google Scholar

[65] View Article

[66] PubMed/NCBI

[67] Google Scholar

[ref20] 20. Wallace AE, Lee R, Mackenzie TA, West AN, Wright S, Booth BM, et al. A longitudinal analysis of rural and urban veterans’ health-related quality of life. J Rural Health. 2010;26(2):156–63. pmid:20447002
View Article
PubMed/NCBI
Google Scholar

[69] View Article

[70] PubMed/NCBI

[71] Google Scholar

[ref21] 21. Proctor SP, Wells TS, Jones KA, Boyco EJ, Smith TC. Examination of post-service health-related quality of life among rural and urban military members of the Millennium Cohort Study. Journal of Rural Social Sciences. 2011;26(3):3.
View Article
Google Scholar

[73] View Article

[74] Google Scholar

[ref22] 22. Hahn MB, Van Wyck R, Lessard L, Fried R. Compounding effects of social vulnerability and recurring natural disasters on mental and physical health. Disaster Med Public Health Prep. 2022;16(3):1013–21. pmid:33757617
View Article
PubMed/NCBI
Google Scholar

[76] View Article

[77] PubMed/NCBI

[78] Google Scholar

[ref23] 23. LaVela SL, Smith B, Weaver FM, Miskevics SA. Geographical proximity and health care utilization in veterans with SCI&D in the USA. Soc Sci Med. 2004;59(11):2387–99. pmid:15450711
View Article
PubMed/NCBI
Google Scholar

[80] View Article

[81] PubMed/NCBI

[82] Google Scholar

[ref24] 24. Long JC, Delamater PL, Holmes GM. Which Definition of Rurality Should I Use?: The relative performance of 8 federal rural definitions in identifying rural-urban disparities. Med Care. 2021;59(Suppl 5):S413–9. pmid:34524237
View Article
PubMed/NCBI
Google Scholar

[84] View Article

[85] PubMed/NCBI

[86] Google Scholar

[ref25] 25. Andrilla CHA, Coulthard C, Patterson DG. Prescribing practices of rural physicians waivered to prescribe buprenorphine. Am J Prev Med. 2018;54(6 Suppl 3):S208–14. pmid:29779544
View Article
PubMed/NCBI
Google Scholar

[88] View Article

[89] PubMed/NCBI

[90] Google Scholar

[ref26] 26. Henning-Smith C, Wu Z, Lahr M. Unmet need for personal care assistance among rural and urban older adults. University of Minnesota. 2019.
View Article
Google Scholar

[92] View Article

[93] Google Scholar

[ref27] 27. Castañeda SF, Belding JN, Kolaja CA, LeardMann CA, Jacobson IG, Rivera AC, et al. Cohort profile update: The US Millennium Cohort Study-evaluating the impact of military experiences on service members and veteran health. Int J Epidemiol. 2023;52(4):e222–31. pmid:37348866
View Article
PubMed/NCBI
Google Scholar

[95] View Article

[96] PubMed/NCBI

[97] Google Scholar

[ref28] 28. Weathers FW, Litz BT, Herman DS, Huska JA, Keane TM. The PTSD Checklist (PCL): Reliability, validity, and diagnostic utility. San Antonio, TX, 1993.
View Article
Google Scholar

[99] View Article

[100] Google Scholar

[ref29] 29. Bliese PD, Wright KM, Adler AB, Cabrera O, Castro CA, Hoge CW. Validating the primary care posttraumatic stress disorder screen and the posttraumatic stress disorder checklist with soldiers returning from combat. J Consult Clin Psychol. 2008;76(2):272–81. pmid:18377123
View Article
PubMed/NCBI
Google Scholar

[102] View Article

[103] PubMed/NCBI

[104] Google Scholar

[ref30] 30. Blanchard EB, Jones-Alexander J, Buckley TC, Forneris CA. Psychometric properties of the PTSD Checklist (PCL). Behav Res Ther. 1996;34(8):669–73. pmid:8870294
View Article
PubMed/NCBI
Google Scholar

[106] View Article

[107] PubMed/NCBI

[108] Google Scholar

[ref31] 31. Kroenke K, Strine TW, Spitzer RL, Williams JBW, Berry JT, Mokdad AH. The PHQ-8 as a measure of current depression in the general population. J Affect Disord. 2009;114(1–3):163–73. pmid:18752852
View Article
PubMed/NCBI
Google Scholar

[110] View Article

[111] PubMed/NCBI

[112] Google Scholar

[ref32] 32. Kroenke K, Spitzer RL, Williams JBW, Löwe B. The patient health questionnaire somatic, anxiety, and depressive symptom scales: A systematic review. Gen Hosp Psychiatry. 2010;32(4):345–59. pmid:20633738
View Article
PubMed/NCBI
Google Scholar

[114] View Article

[115] PubMed/NCBI

[116] Google Scholar

[ref33] 33. Spitzer RL, Kroenke K, Williams JB, Group PHQPCS, Group PHQPCS. Validation and utility of a self-report version of PRIME-MD: The PHQ primary care study. JAMA. 1999;282(18):1737–44.
View Article
Google Scholar

[118] View Article

[119] Google Scholar

[ref34] 34. Ware JE, Gandek B, Kosinski M, Aaronson NK, Apolone G, Brazier J, et al. The equivalence of SF-36 summary health scores estimated using standard and country-specific algorithms in 10 countries: Results from the IQOLA Project. International Quality of Life Assessment. J Clin Epidemiol. 1998;51(11):1167–70. pmid:9817134
View Article
PubMed/NCBI
Google Scholar

[121] View Article

[122] PubMed/NCBI

[123] Google Scholar

[ref35] 35. WWAMI Rural Health Research Center. RUCA data: using RUCA data 2010.http://depts.washington.edu/uwruca/ruca-uses.php

[ref36] 36. CDC/ATSDR Social Vulnerability Index. https://www.atsdr.cdc.gov/placeandhealth/svi/data_documentation_download.html. 2020.

[ref37] 37. HERC’s Medicare Wage Index for VA Facilities. https://www.herc.research.va.gov/include/page.asp?id=guidebook-wage-index. 2023.

[ref38] 38. Porter B, Hoge CW, Tobin LE, Donoho CJ, Castro CA, Luxton DD, et al. Measuring aggregated and specific combat exposures: Associations between combat exposure measures and posttraumatic stress disorder, depression, and alcohol-related problems. J Trauma Stress. 2018;31(2):296–306. pmid:29603393
View Article
PubMed/NCBI
Google Scholar

[128] View Article

[129] PubMed/NCBI

[130] Google Scholar

[ref39] 39. National Center for Health Statistics. Health, United States, 2019. 2021.

[ref40] 40. Jacobson IG, Horton JL, Smith B, Wells TS, Boyko EJ, Lieberman HR, et al. Bodybuilding, energy, and weight-loss supplements are associated with deployment and physical activity in U.S. military personnel. Ann Epidemiol. 2012;22(5):318–30. pmid:22445519
View Article
PubMed/NCBI
Google Scholar

[133] View Article

[134] PubMed/NCBI

[135] Google Scholar

[ref41] 41. Organization WH. WHOQOL user manual. Division of mental health and prevention of substance abuse. World Health Organization. 2013.

[ref42] 42. Boscarino JJ, Figley CR, Adams RE, Urosevich TG, Kirchner HL, Boscarino JA. Mental health status in veterans residing in rural versus non-rural areas: Results from the veterans’ health study. Mil Med Res. 2020;7(1):44. pmid:32951600
View Article
PubMed/NCBI
Google Scholar

[138] View Article

[139] PubMed/NCBI

[140] Google Scholar

[ref43] 43. Breslau J, Marshall GN, Pincus HA, Brown RA. Are mental disorders more common in urban than rural areas of the United States?. J Psychiatr Res. 2014;56:50–5. pmid:24857610
View Article
PubMed/NCBI
Google Scholar

[142] View Article

[143] PubMed/NCBI

[144] Google Scholar

[ref44] 44. Ramchand R, Rudavsky R, Grant S, Tanielian T, Jaycox L. Prevalence of, risk factors for, and consequences of posttraumatic stress disorder and other mental health problems in military populations deployed to Iraq and Afghanistan. Curr Psychiatry Rep. 2015;17(5):37. pmid:25876141
View Article
PubMed/NCBI
Google Scholar

[146] View Article

[147] PubMed/NCBI

[148] Google Scholar

[ref45] 45. Cully JA, Jameson JP, Phillips LL, Kunik ME, Fortney JC. Use of psychotherapy by rural and urban veterans. J Rural Health. 2010;26(3):225–33. pmid:20633090
View Article
PubMed/NCBI
Google Scholar

[150] View Article

[151] PubMed/NCBI

[152] Google Scholar

[ref46] 46. Fischer EP, McCarthy JF, Ignacio RV, Blow FC, Barry KL, Hudson TJ, et al. Longitudinal patterns of health system retention among veterans with schizophrenia or bipolar disorder. Community Ment Health J. 2008;44(5):321–30. pmid:18401711
View Article
PubMed/NCBI
Google Scholar

[154] View Article

[155] PubMed/NCBI

[156] Google Scholar

[ref47] 47. Hudson TJ, Fortney JC, Williams JS, Austen MA, Pope SK, Hayes CJ. Effect of rural residence on use of VHA mental health care among OEF/OIF veterans. Psychiatr Serv. 2014;65(12):1420–5. pmid:25081581
View Article
PubMed/NCBI
Google Scholar

[158] View Article

[159] PubMed/NCBI

[160] Google Scholar

[ref48] 48. Spoont M, Greer N, Su J, Fitzgerald P, Rutks I, Wilt T. Rural vs. urban ambulatory health care: A systematic review. 2011.

[ref49] 49. Teich J, Ali MM, Lynch S, Mutter R. Utilization of mental health services by veterans living in rural areas. J Rural Health. 2017;33(3):297–304. pmid:27701791
View Article
PubMed/NCBI
Google Scholar

[163] View Article

[164] PubMed/NCBI

[165] Google Scholar

[ref50] 50. Jansen SJT. Urban, suburban or rural? Understanding preferences for the residential environment. Journal of Urbanism: International Research on Placemaking and Urban Sustainability. 2020;13(2):213–35.
View Article
Google Scholar

[167] View Article

[168] Google Scholar

[ref51] 51. Franks JA, Davis ES, Bhatia S, Kenzik KM. Defining rurality: An evaluation of rural definitions and the impact on survival estimates. J Natl Cancer Inst. 2023;115(5):530–8. pmid:36762829
View Article
PubMed/NCBI
Google Scholar

[170] View Article

[171] PubMed/NCBI

[172] Google Scholar

[ref52] 52. Yoo E-H, Roberts JE, Eum Y, Li X, Konty K. Exposure to urban green space may both promote and harm mental health in socially vulnerable neighborhoods: A neighborhood-scale analysis in New York City. Environ Res. 2022;204(Pt C):112292. pmid:34728238
View Article
PubMed/NCBI
Google Scholar

[174] View Article

[175] PubMed/NCBI

[176] Google Scholar

[ref53] 53. Meyer OL, Castro-Schilo L, Aguilar-Gaxiola S. Determinants of mental health and self-rated health: A model of socioeconomic status, neighborhood safety, and physical activity. Am J Public Health. 2014;104(9):1734–41. pmid:25033151
View Article
PubMed/NCBI
Google Scholar

[178] View Article

[179] PubMed/NCBI

[180] Google Scholar

[ref54] 54. Moore THM, Kesten JM, López-López JA, Ijaz S, McAleenan A, Richards A, et al. The effects of changes to the built environment on the mental health and well-being of adults: Systematic review. Health Place. 2018;53:237–57. pmid:30196042
View Article
PubMed/NCBI
Google Scholar

[182] View Article

[183] PubMed/NCBI

[184] Google Scholar

[ref55] 55. Richardson R, Westley T, Gariépy G, Austin N, Nandi A. Neighborhood socioeconomic conditions and depression: A systematic review and meta-analysis. Soc Psychiatry Psychiatr Epidemiol. 2015;50(11):1641–56. pmid:26164028
View Article
PubMed/NCBI
Google Scholar

[186] View Article

[187] PubMed/NCBI

[188] Google Scholar

[ref56] 56. Buzza C, Ono SS, Turvey C, Wittrock S, Noble M, Reddy G, et al. Distance is relative: Unpacking a principal barrier in rural healthcare. J Gen Intern Med. 2011;26 Suppl 2(Suppl 2):648–54. pmid:21989617
View Article
PubMed/NCBI
Google Scholar

[190] View Article

[191] PubMed/NCBI

[192] Google Scholar

[ref57] 57. Goins RT, Williams KA, Carter MW, Spencer M, Solovieva T. Perceived barriers to health care access among rural older adults: A qualitative study. J Rural Health. 2005;21(3):206–13. pmid:16092293
View Article
PubMed/NCBI
Google Scholar

[194] View Article

[195] PubMed/NCBI

[196] Google Scholar

[ref58] 58. Fink DS, Stohl M, Mannes ZL, Shmulewitz D, Wall M, Gutkind S, et al. Comparing mental and physical health of U.S. veterans by VA healthcare use: implications for generalizability of research in the VA electronic health records. BMC Health Serv Res. 2022;22(1):1500. pmid:36494829
View Article
PubMed/NCBI
Google Scholar

[198] View Article

[199] PubMed/NCBI

[200] Google Scholar

[ref59] 59. Meffert BN, Morabito DM, Sawicki DA, Hausman C, Southwick SM, Pietrzak RH. US veterans who do and do not utilize veterans affairs health care services: demographic, military, medical, and psychosocial characteristics. The Primary Care Companion for CNS Disorders. 2019;21(1):26992.
View Article
Google Scholar

[202] View Article

[203] Google Scholar

[ref60] 60. Nelson KM, Starkebaum GA, Reiber GE. Veterans using and uninsured veterans not using Veterans Affairs (VA) health care. Public Health Rep. 2007;122(1):93–100. pmid:17236614
View Article
PubMed/NCBI
Google Scholar

[205] View Article

[206] PubMed/NCBI

[207] Google Scholar

[ref61] 61. Porter B, Dozier ME, Seelig AD, Zhu Y, Patoilo MS, Boyko EJ, et al. Posttraumatic stress disorder, Veterans Health Administration use, and care-seeking among recent-era U.S. veterans. J Trauma Stress. 2024;37(3):460–70. pmid:38424733
View Article
PubMed/NCBI
Google Scholar

[209] View Article

[210] PubMed/NCBI

[211] Google Scholar

[ref62] 62. Sayer NA, Orazem RJ, Noorbaloochi S, Gravely A, Frazier P, Carlson KF, et al. Iraq and afghanistan war veterans with reintegration problems: Differences by veterans affairs healthcare user status. Adm Policy Ment Health. 2015;42(4):493–503. pmid:24913102
View Article
PubMed/NCBI
Google Scholar

[213] View Article

[214] PubMed/NCBI

[215] Google Scholar

[ref63] 63. Maynard C, Nelson K. Compensation for veterans with service connected disabilities: Current findings and future implications. Journal of Disability Policy Studies. 2020;31(1):57–62.
View Article
Google Scholar

[217] View Article

[218] Google Scholar

[ref64] 64. Bovin MJ, Resnik J, Linsky AM, Stolzmann K, Mull HJ, Schnurr PP, et al. Does screening for PTSD lead to VA mental health care? Identifying the spectrum of initial VA screening actions. Psychol Serv. 2023;20(3):525–32. pmid:35446094
View Article
PubMed/NCBI
Google Scholar

[220] View Article

[221] PubMed/NCBI

[222] Google Scholar

Figures

Abstract

Background

Methods

Results

Discussion

Introduction

Methods

Study population

Measures

Mental health outcomes.

Health care utilization.

Residential location characteristics.

Covariates.

Statistical analysis

Results

Descriptive results

Bivariate associations

Adjusted associations

Supplemental analyses

Discussion

Supporting information

S1 Table. Associations between risk and protective factors with Time 2 mental health outcomes among Veteran Millennium Cohort Study participants as included in adjusted models in Table 2, n = 20,423.

S2 Table. Associations between continuous rurality and mental health outcomes, n = 20,418.

Acknowledgments

References