Servicewomen in abortion-restricted states have a significant geographic burden to access abortion care.
Abstract
OBJECTIVE:
To quantify geographic accessibility to abortion services for servicewomen in the continental United States after the Dobbs v. Jackson Women's Health Organization decision.
METHODS:
We extracted ZIP code of residence for 203,139 servicewomen (18–49 years of age) from the Military Health System Data Repository in December 2024. We performed point density analyses and spatiotemporal network modeling of servicewomen's locations and distance to 389 geocoded abortion clinics using ArcGIS Pro. We calculated travel times to abortion clinics by state-level legal restrictions (most restrictive, restrictive, and somewhat/protective based on the Guttmacher Institute state abortion restriction categories) and geographic region. We estimated mean driving times and the proportion of servicewomen within 30-, 60-, and 90-minute travel-time thresholds.
RESULTS:
Mean driving time to the nearest clinic for the 193,029 successfully geocoded servicewomen was 164.1 minutes. More than half (55.5%) required more than 90 minutes of travel time, and 8.5% lived within 30 minutes. Mean driving time was significantly higher in the most restrictive states (381.7 minutes) compared with restrictive states (118.9 minutes, difference of means 262.8, 95% CI, 260.1–265.5) and to somewhat/protective states (68.7 minutes, difference of means 313.1, 95% CI, 310.7–315.4). Of 47,672 servicewomen stationed in most restrictive states, 99.7% required travel times exceeding 90 minutes compared with 60.1% (n=41,811) in restrictive states (odds ratio [OR 0.51], 95% CI, 0.50–0.53) and 23.5% (n=17,846) in somewhat/protective states (OR 0.27, 95% CI, 0.26–0.28). Servicewomen in Western Interior and South regions averaged almost 3 and more than 7 hours of travel time for care, respectively. Travel time exceeded 90 minutes for over 99% in the South and for the majority in the Western Interior (90.1%), East Coast (62.7%), and Midwest (54.7%).
CONCLUSION:
Over half of reproductive-aged servicewomen in the continental United States face significant travel burdens to access abortion services. One-quarter reside in banned states with nearly universal geographic constraints. Current legal and policy environments create substantial structural differences that may affect servicewomen's reproductive health.
Abortion access within the Military Health System is uniquely dictated by federal law. Under the Hyde Amendment, abortion is a covered health service only in cases of rape or incest or when the pregnant individual's life is endangered.1 Active-duty servicewomen requiring care outside these exceptions rely on care outside the Military Health System and pay out of pocket while navigating individual state laws. The 2022 Dobbs v. Jackson Women's Health Organization U.S. Supreme Court decision moved abortion legality to the state level, and 13 states now have near-total abortion bans, and the remaining states range from limiting the procedure to early pregnancy (eg, 6 or 12 weeks) to including stipulations that make obtaining an abortion more difficult to explicitly protecting access through state constitutions and statutes.2
Approximately 80,000 servicewomen are now stationed in states with abortion bans or severe restrictions.3 As a result, servicewomen's access to abortion care is influenced by duty station and financial means. With women representing the fastest-growing demographic in the military, these constraints not only affect individual service member health but also present a broader military readiness issue3 and potentially increase costs to the military through increasing adverse maternal and neonatal outcomes associated with limiting abortion care.4 This study investigates the time required for servicewomen to travel to abortion clinics after the Dobbs decision, providing data that reflect the potential realities of active-duty servicewomen and may inform policy decisions to optimize military readiness.
METHODS
We queried the Military Health System Data Repository for all active-duty servicewomen 18–49 years of age with a five-digit ZIP code of residence in the continental United States in December 2024. The Military Health System Data Repository contains electronic health and demographic information for all U.S. service members and their beneficiaries. The Uniformed Services University IRB granted approval.
We performed demographic accessibility modeling to further assess how accessibility constraints manifest across demographic and occupational strata within the military population. We queried the Military Health System Data Repository for relevant demographic information, including marital status (married or unmarried), age categorized into seven groups (18–20, 21–24, 25–29, 30–34, 35–39, 40–44, 45–49 years), military rank, branch of service, race and ethnicity, and ZIP code of residence. We categorized rank as junior enlisted, senior enlisted, or officer based on the military rank structure. Rank can serve as a proxy for education and income. Junior enlisted personnel generally have lower education levels and income than officers and senior enlisted personnel; however, all service members have the same level of coverage for medical care.5,6 Four race and ethnicity groups were used as self-reported in the Military Health System Data Repository: Hispanic, Non-Hispanic Black, Non-Hispanic White, and additional races and ethnicities. The additional races and ethnicities category included Asian and Pacific Islander, American Indian and Alaska Native, and multiracial individuals. We included race and ethnicity to determine whether certain racial or ethnic groups within the military population face disproportionately greater travel burdens. To prevent patient identification, if any geographic unit formed by combining all ZIP codes with the same three initial digits contained fewer than 20,000 people, we changed the initial three digits of the ZIP code to 000. Aggregated data reflected the number of servicewomen in a ZIP code who fit the specified demographic criteria.
The abortion clinic locations were initially extracted from the dataset reported by Alterio et al7 in 2023 and geocoded with the U.S. Census Bureau Geocoder.8 These geocoded data records were then systematically cross-referenced with four patient-facing web-based directories—Planned Parenthood's clinic locator, the National Abortion Federation provider directory, Abortion Finder, and Power to Decide—to update abortion clinics as of December 2024. We validated abortion clinics with available state health department licensing records. A total of 389 listed and verified clinics were used for all spatial analyses.
We used the abortion restriction categories developed by The Guttmacher Institute, which maintains seven state abortion restriction levels based on approximately 20 types of abortion restrictions and 10 protective policies across states and based on the methodology of Harper et al9 to group these categories into three restriction levels. Using the Guttmacher Institute restriction categorizations of state-level abortion restrictions as of December 2024, we grouped states into three levels of abortion restrictions: 1) most restrictive; 2) restrictive, defined as states categorized as “very restrictive” or “restrictive”; and 3) somewhat/protective, defined as states with “some restrictions/protections” or higher levels of protection in the Guttmacher system10 (Fig. 1).
Fig. 1. State abortion restriction levels and geographic regions. WC, West Coast; WI, Western Interior; SI, South; MW, Midwest; EC, East Coast; NA, North Atlantic.
Cherikh. Geospatial Analysis Military Abortion Access. O&G Open 2026.
We also stratified the continental United States into six geographic regions—North Atlantic, East Coast, Midwest, West Coast, South, and Western Interior—to capture systematic variation in population density, urban form, physical geography, and transportation infrastructure that are known to shape health care accessibility. These regions distinguish high-density urban and peri-urban corridors from predominantly rural, plains-based, and mountainous landscapes, which impose different travel-time constraints and routing efficiencies.11,12 Such stratification reduces confounding in spatial relationships and enables realistic comparisons of travel time–based access to time-sensitive reproductive health services across heterogeneous policy and geographic landscapes, where travel time is the most relevant accessibility metric.13,14
We first evaluated the clustering of servicewomen and abortion clinic locations per area ZIP code using the Point Density tool within the Spatial Analyst geoprocessing toolbox in ArcGIS Pro. For servicewomen, we applied a weighted point density approach, integrating both the number of servicewomen at each area ZIP code of residence and the proximity of these ZIP codes to one another. Points with larger servicewomen populations and shorter interpoint distances contributed to higher density estimates, enabling us to identify regions where servicewomen are most spatially concentrated. We used this weighting approach because the effect of clinic availability is magnified in areas with high concentrations of servicewomen, where restricted access may have a greater influence on operational readiness and demand for medical support. Similarly, we generated weighted density surfaces for abortion clinics using facility locations. The density values were driven solely by the spatial arrangement and distance between the clinics, allowing us to map areas with abundant versus sparse service availability within each ZIP code. Comparing servicewomen densities with facility densities provides a spatially explicit measure of accessibility gaps, especially in areas with restricted access to abortion facilities.
Second, we estimated the driving distances and times from servicewomen ZIP codes to the nearest clinic services. We conducted spatiotemporal network analysis across different times of 7 d/wk from 8 am to 10 pm, accounting for traffic flow patterns and traffic conditions during potential clinic opening hours, including peak and off-peak hours,15,16 using the ArcGIS Network Analyst extension with the StreetMap Premium North America dataset.17 This dataset incorporates time-of-day speed profiles based on average observed speeds across 5-minute intervals per day of week, derived from historical traffic data on individual road segments. Accordingly, we calculated average travel distances/times between the ZIP code areas of servicewomen and the nearest abortion clinic using the national roads dataset of 15,876 segments from the U.S. Census Bureau.8
The route distances between servicewomen area codes and nearest clinic were categorized into four travel time-time bins—0–30, >30–60, >60–90, and>90 minutes—based on prior research demonstrating that travel time rather than distance is the most relevant accessibility metric in reproductive health care.18,19 These four travel-time frameworks were adopted from prior work characterizing post-Dobbs abortion access in the U.S. general population.7 The 90-minute threshold was selected a priori on the basis of prior reproductive health care access research showing that this boundary represents a significant geographic constraint to abortion services, beyond which health care use declines markedly.20 We defined high-density zones as regions where servicewomen and abortion clinics were clustered within 30-minute network-travel proximity. Low-medium–density zones were defined as regions where servicewomen and abortion clinics were clustered within 60- or 90-minute network-travel proximity. Meanwhile, low-density zones included regions where the counts of servicewomen and abortion clinics were randomly distributed within more than 90-minute network-travel proximity. These zones enabled us to identify locations where servicewomen are likely to experience the least or greatest geographic restriction to care.
Differences in mean travel time between state restriction levels and between geographic regions were calculated with the Welch two-sample t test (two tailed, α=0.05), which does not assume equal variances across groups. Poisson regression was used to estimate odds of being more than 90 minutes away from the closest clinic by state restriction level and geographic region, using an α of 0.05 to define statistical significance.
To evaluate the accessibility constraints across demographic and occupational strata within the military population, we used a linear regression in SAS 9.4 to regress all travel-time estimates against key individual and service-level characteristics, including age, marital status, race and ethnicity, rank, and branch of military service. Assumptions for linear regression were performed and met, including test of normality, independent observations, and constant variance. Weights were also accounted for in the analyses using the aggregated data point that reflects the number of servicewomen in a ZIP code who fit the specified demographic criteria. We excluded servicewomen with missing/incomplete data. We used a two-tailed α of 0.05 to define statistical significance.
RESULTS
Of 203,139 identified servicewomen, 193,029 were successfully geocoded and included in our analyses. A total of 10,110 locations could not be successfully geocoded because of missing/incomplete data (n=97) or ZIP codes outside the continental United States (n=10,013). The majority (76.5%) were enlisted servicewomen, and about half were married. The Air Force, Army, and Navy service branches each made up approximately 30% of the cohort. Appendix 1 (available online at http://links.lww.com/AOG/E694) outlines the demographics of the cohort.
The point density analyses identified locations with high-density zones of abortion clinics and servicewomen (Figs. 2 and 3). High-clinic-density zones overlapped with high-servicewomen-density zones in Georgia, Northern Virginia, and New York. There were low-medium–density zones of clinics across the United States, more commonly on the East Coast and sparsely throughout the Midwest.
Fig. 2. Point density map of servicewomen locations. Blue circles indicate abortion clinic locations, and green points indicate servicewomen locations. Red highlight indicates high density of servicewomen, and yellow highlight indicates low–medium density of servicewomen.
Cherikh. Geospatial Analysis Military Abortion Access. O&G Open 2026.
Fig. 3. Point density map of abortion clinic locations. Blue circles indicate abortion clinic locations, and green points indicate servicewomen locations. Red highlight indicates high density of abortion clinics, and yellow highlight indicates low–medium density of abortion clinics.
Cherikh. Geospatial Analysis Military Abortion Access. O&G Open 2026.
Among the entire population, the mean driving time to the nearest abortion clinic was 164.1 minutes. Mean driving time was significantly higher in most restrictive states (381.7 minutes) compared with restrictive states (118.9 minutes, difference of means 262.8, 95% CI, 260.1–265.5) and somewhat/protective states (68.7 minutes, difference of means 313.1, 95% CI, 310.7–315.4) (Table 1).
Table 1.
Travel Times to Nearest Abortion Clinic Overall and by State Restriction Level for Active-Duty Servicewomen 18–49 Years of Age in the Continental United States, December 2024
| Travel Time (min) | Overall (N=193,029) | Most Restrictive (n=47,672) | Restrictive (n=69,528) | Somewhat/Protective (n=75,829) | ||||
| 0–30 | 16,327 (8.5) | 24.1±5.6 | 32 (0.1) | 16.9±5.9 | 4,393 (6.3) | 17.8±4.2 | 11,902 (15.7) | 26.5±4.0 |
| More than 30–60 | 43,847 (22.7) | 41.2±7.6 | 46 (0.1) | 44.2±8.3 | 9,449 (13.6) | 42.6±7.6 | 34,352 (45.3) | 40.8±7.6 |
| More than 60–90 | 25,682 (13.3) | 70.8±8.2 | 78 (0.2) | 78.2±7.8 | 13,875 (20.0) | 72.1±8.1 | 11,729 (15.5) | 69.2±8 |
| More than 90 | 107,173 (55.5) | 258±177 | 47,516 (99.7%) | 382.8±188.3 | 41,811 (60.1) | 162.3±82.6 | 17,846 (23.5) | 150±55.7 |
| Overall | 164.1±282.2 | 381.7±320.6 | 118.9±143.7 | 68.7±54.4 | ||||
| Difference of means | Reference | 262.8 (260.1–265.5) | 313.1 (310.7–315.4) | |||||
Data are presented as n (%), mean±SD, or mean (95% CI).
Although 16,327 servicewomen (8.5%) required less than 30 minutes travel time to the closest abortion clinic, 107,173 (55.5%) required more than 90 minutes (Table 1). Of the 47,672 women in most restrictive states, 99.7% required more than 90 minutes travel time. In contrast, 41,811 servicewomen (60.1%) in restrictive states and 17,846 (23.5%) in somewhat/protective states required more than 90 minutes (Table 1). Compared with most restrictive states, the odds of requiring more than 90 minutes travel were lower among servicewomen in restrictive states (OR 0.51, 95% CI, 0.50–0.53) and in somewhat/protective states (OR 0.27, 95% CI, 0.26–0.28).
Average travel time to the nearest abortion clinic differed significantly across geographic regions, with mean driving time highest in the South (444.1±166.6 minutes). Mean travel times in the Western Interior (177.9±79.7 minutes), Midwest (140.2±106.9 minutes), and East Coast (110.5±66.4 minutes) ranged from approximately 2 to 3 hours. In contrast, servicewomen in the North Atlantic and West Coast averaged 49.7±21.1 and 46.3±27.9 minutes, respectively. Mean driving times were higher in the South compared with the West Coast (difference of means 397.8, 95% CI, 394.4–400.7), North Atlantic (difference of means 394.4, 95% CI, 391.5–397.4), East Coast (difference of means 333.6, 95% CI, 330.5–336.6), Midwest (difference of means 303.9, 95% CI, 299.8–307.9), and Western Interior (difference of means 266.2, 95% CI, 262.8–269.7) (Table 2).
Table 2.
Travel Times to Nearest Abortion Clinic by Region for Active-Duty Servicewomen 18–49 Years of Age in the Continental United States, December 2024
| Travel Time (min) | West Coast (N=37,565) | North Atlantic (n=19,701) | Midwest (n=15,161) | East Coast (n=66,046) | Western Interior (n=17,625) | South (n=36,931) | ||||||
| 0–30 | 9,619 (25.6) | 27.5±3.2 | 2,195 (11.1) | 22.4±3.6 | 1,432 (9.4) | 13.7±3.0 | 3,074 (4.7) | 19.6±3.3 | 7 (0.0) | 10.9±8.5 | 0 (0.0) | — |
| More than 30–60 | 19,482 (51.9) | 36.5±5.1 | 14,703 (74.6) | 46.5±6.5 | 787 (5.2) | 49.1±6.9 | 8,479 (12.8) | 41.7±7.2 | 396 (2.2) | 51.9±2.9 | 0 (0.0) | — |
| More than 60–90 | 4,507 (12.0) | 69.7±8.3 | 2,076 (10.5) | 75.4±3.2 | 4,644 (30.6) | 67.1±7.7 | 13,121 (19.9) | 72.3±8.3 | 1,334 (7.6) | 65.7±5.3 | 0 (0.0) | — |
| More than 90 | 3,957 (10.5) | 114.1±24.3 | 725 (3.7) | 123.3±37.6 | 8,298 (54.7) | 211.6±96.1 | 41,408 (62.7) | 143.5±62.2 | 15,888 (90.1) | 190.5±73.7 | 36,895 (100.0) | 444.1±166.6 |
| Average | 46.3±27.9 | 49.7±21.1 | 140.2±106.9 | 110.5±66.4 | 177.9±79.7 | 444.1±166.6 | ||||||
| Difference of means | 397.8 (398.4–400.7) | 394.4 (391.5–397.4) | 303.9 (299.8–307.9) | 333.6 (330.5–336.6) | 266.2 (262.8–269.7) | Ref | ||||||
Ref, reference.
Data are presented as n (%), mean±SD, or mean (95% CI).
The majority of servicewomen in the South, Western Interior, East Coast, and Midwest exceeded the 90-minute travel threshold (100.0%, 90.1%, 62.7%, and 54.7%, respectively). In contrast, the majority of servicewomen in the North Atlantic and West Coast (63.9% and 85.7%, respectively) lived within 30–60 minutes of a clinic (Table 2). Compared with the South region, the odds of requiring more than 90 minutes of travel were lower for servicewomen in the Western Interior (OR 0.96, 95% CI, 0.96–0.99), Midwest (OR 0.63, 95% CI, 0.06–0.65), East Coast (OR 0.51, 95% CI, 0.50–0.52), North Atlantic (OR 0.07, 95% CI, 0.07–0.08), and West Coast (OR 0.15, 95% CI, 0.14–0.15).
In multivariable linear regression adjusted for age, marital status, race and ethnicity, rank, and branch of service, all age groups had shorter mean travel times to the nearest abortion clinic compared with servicewomen 18–20 years of age (Appendix 2, http://links.lww.com/AOG/E694). Officers and senior enlisted had shorter mean travel time compared with junior enlisted. Hispanic servicewomen had longer mean travel time than Non-Hispanic White individuals, whereas servicewomen in the additional races and ethnicities category had shorter mean travel time compared with Non-Hispanic White individuals. Married servicewomen had shorter mean travel time than nonmarried servicewomen. Compared with Army servicewomen, those in the Coast Guard, Public Health Service, Marines, Navy, National Atmospheric and Oceanic Administration, and Space Force had shorter mean travel times, whereas Air Force servicewomen had longer mean travel time (Appendix 2, http://links.lww.com/AOG/E694).
DISCUSSION
This study provides a comprehensive geospatial assessment of abortion access for servicewomen in the continental United States in the setting of the national abortion restriction landscape after the 2022 Dobbs decision. Using an integrated spatial-analytic framework that combines census data, spatiotemporal road–network modeling, and demographic accessibility analysis, we demonstrate the significant contributions of state policy environment and duty station geography to abortion access for servicewomen. More than half of servicewomen nationwide required more than 90 minutes of travel to reach the nearest abortion clinic, and nearly all servicewomen stationed in most restrictive states faced travel times exceeding this threshold. These findings indicate that abortion restrictions function not merely as legal constraints but as structural determinants of health care access within the Military Health System.
Our findings are consistent with U.S. general population studies documenting substantial increases in travel time and geographic isolation after Dobbs.18,20,21 Civilian populations face many of the same challenges as military populations, including lack of insurance coverage, state-level restrictions, and geographic constraints. However, servicewomen experience these constraints in a unique context. Unlike civilian populations, servicewomen have limited autonomy over their place of residence, restricted ability to take leave, and specific concerns regarding confidentiality and command notification. As a result, travel time reflects not only physical distance but also the cumulative administrative, occupational, and psychosocial burdens associated with accessing care.
The extreme travel burden observed among servicewomen in most restrictive states and the South (where most states have total abortion bans) underscores how state-level abortion policy has become a primary driver of access within a federal health care system. Even in somewhat/protective states, where average travel times were shorter, a substantial proportion of servicewomen still faced journeys exceeding 1 hour, a threshold previously shown to reduce health care use and delay time-sensitive services in the civilian population.14,22 Previous studies in civilian populations have also shown that longer travel distances are associated with increased financial hardship and a higher likelihood of continuing an unwanted pregnancy.19,21 For military populations with constrained mobility and no insurance coverage for most abortion services, the geographic constraints we report likely reflect a significant challenge to abortion access. Our findings are also relevant for military dependents, who face the same insurance and geographic constraints.
The implications of these access concerns extend beyond individual health outcomes to military readiness and force sustainability. Delays in abortion care are associated with increased medical risk, higher costs, and more complex clinical management.23,24 Within the military, prolonged travel for health care can disrupt training cycles, reduce unit availability, and increase administrative burden for commanders and medical staff.25 These effects are likely to be disproportionately borne by junior enlisted servicewomen, for whom rank serves as a proxy for income, job flexibility, and access to private transportation and who are at higher risk for unintended pregnancy compared with other servicewomen.26 We found that junior enlisted, nonmarried, and the youngest servicewomen would encounter greater average travel time to abortion services, highlighting that women who may be most affected by abortion restrictions also face disproportionate constraints to receive care. Air Force and Army servicewomen also are located relatively greater distances to abortion services, underscoring that structural factors related to military service affect care delivery.
This study has several strengths, including its national scope, use of individual-level demographic data, and integration of multiple spatial-analytic methods to capture both structural and experiential dimensions of access. Nevertheless, limitations should be acknowledged. Clinic availability and capacity are dynamic and may change rapidly in response to changes in states laws and operational pressures. Our analysis does not account for appointment wait times, cross-border demand surges, travel by modality other than driving, or patient circumstances that may lead individuals to bypass closer facilities. We also are unable to account for how the availability of telehealth abortion services may mitigate some geographic abortion access constraints. Our clinic dataset was derived from four patient-facing web-based directories that reflect dedicated abortion providers with confirmed physical addresses. This count does not include hospitals, physician offices, and nonspecialized outpatient facilities that perform abortions along with other services but are not listed in patient-facing directories. Actual access may be slightly less constrained if proximity to uncatalogued abortion providers is considered. Nonetheless, restricting the analysis to publicly identifiable, patient-facing clinic locations reflects the information available to servicewomen seeking care, which is the access experience most relevant to this population. Finally, we did not directly measure abortion use or clinical outcomes, limiting inference about the downstream health effects of geographic constraints.
In the post-Dobbs era, military abortion access is profoundly shaped by state policy environments and duty station geography. Our findings demonstrate that a majority of servicewomen face substantial travel burdens that challenge timely access to reproductive health care. Addressing geographic constraints in abortion access for servicewomen will require policy solutions that acknowledge the unique considerations of military service and align reproductive health care access with evidence-based standards of care.
Footnotes
Financial Disclosure The authors did not report any potential conflicts of interest.
Disclaimer: The opinions and assertions expressed herein are those of the authors and do not reflect the official policy or position of the Department of the Navy, the Uniformed Services University of the Health Sciences, or the Department of War.
Each author has confirmed compliance with the journal's requirements for authorship.
Peer reviews and author correspondence are available at http://links.lww.com/AOG/E695.
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