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Figure 1.  Travel Time to Nearest US Abortion Facility Before and After Dobbs v Jackson Women’s Health US Supreme Court Decision
Travel Time to Nearest US Abortion Facility Before and After Dobbs v Jackson Women’s Health US Supreme Court Decision

Facilities as listed in the Advancing New Standards in Reproductive Health database; 82 892 census tracts included. B and C, States with bans are outlined: Alabama, Arizona, Arkansas, Florida (15-wk gestational limit), Georgia (6-wk limit), Idaho, Kentucky, Louisiana, Mississippi, Missouri, North Carolina (20-wk limit), Oklahoma, South Dakota, Tennessee, Texas, Utah (18-wk limit), West Virginia, and Wisconsin. Maps are shown with US National Atlas equal-area projection to depict the 3D size and shape of each tract proportionally, thus larger areas may have smaller populations.

Figure 2.  Change in Distribution of Travel Time From US Census Tracts to Nearest Abortion Facility Before and After Dobbs v Jackson Women’s Health US Supreme Court Decision
Change in Distribution of Travel Time From US Census Tracts to Nearest Abortion Facility Before and After Dobbs v Jackson Women’s Health US Supreme Court Decision

Travel time to nearest abortion site from 82 892 census tracts in the contiguous US by state. Distributions represent the density of census tracts at each respective travel cutoff. The pre-Dobbs period includes travel to all facilities providing abortions in 2021. The post-Dobbs period removed facilities in the 15 states with total or 6-week abortion bans as of September 30, 2022. States with bans (total ban in effect unless otherwise noted) include Alabama, Arizona, Arkansas, Georgia (6-week gestational limit), Idaho, Kentucky, Louisiana, Mississippi, Missouri, Oklahoma, South Dakota, Tennessee, Texas, West Virginia, and Wisconsin. Florida (15-week gestational limit), Utah (18-week gestational limit), and North Carolina (20-week gestational limit) were included in the group of states without total or 6-week abortion bans. Distributions are stratified to show census tracts in each state with a total or 6-week abortion ban separately and all census tracts in states without total or 6-week bans in a single distribution. Distributions are ordered along the y-axis by total estimated population of females aged 15 to 44 years. All distributions were weighted by the population of females aged 15 to 44 years. Travel time distributions are smoothed to 3-minute bins. Alaska and Hawaii were excluded due to the unique challenges of spatial access in these states.

Figure 3.  Change in US Females of Reproductive Age Living in a Census Tract More Than 60 Minutes From an Abortion Facility Before and After Dobbs v Jackson Women’s Health US Supreme Court Decision
Change in US Females of Reproductive Age Living in a Census Tract More Than 60 Minutes From an Abortion Facility Before and After Dobbs v Jackson Women’s Health US Supreme Court Decision

Percentage and percentage point change (sensitivity interval [SI]) of US females of reproductive age (15-44 years) living in census tracts more than 60 minutes from an abortion facility, estimated from a repeated cross-sectional spatial analysis. The pre-Dobbs period was modeled to assume all facilities providing abortions in 2021 were active. The post-Dobbs period was modeled after removing facilities in the 15 states with total or 6-week abortion bans as of September 30, 2022. Demographic estimates drawn from the 2016-2020 American Community Survey. Median household income from this census was estimated to be $67 521.

Table.  US Census Tract Demographics From the 2020 American Community Survey by Travel Time to Nearest Abortion Facility After Dobbs v Jackson Women’s Health US Supreme Court Decision on June 24, 2022a,b
US Census Tract Demographics From the 2020 American Community Survey by Travel Time to Nearest Abortion Facility After Dobbs v Jackson Women’s Health US Supreme Court Decision on June 24, 2022a,b
1.
Dobbs v Jackson Women’s Health Organization_ US _ (June 24, 2022). Accessed October 25, 2022. https://www.supremecourt.gov/opinions/21pdf/19-1392_6j37.pdf
2.
McCann  A, Walker  AS, Sasani  A, Johnston  T, Buchanan  L, Huang  J. Tracking the states where abortion is now banned. New York Times. Updated September 30, 2022. Accessed October 13, 2022. https://www.nytimes.com/interactive/2022/us/abortion-laws-roe-v-wade.html
3.
Jerman  J, Jones  RK, Onda  T. Characteristics of US abortion patients in 2014 and changes since 2008. Guttmacher Institute. May 2016. Accessed October 24, 2022. https://www.guttmacher.org/report/characteristics-us-abortion-patients-2014
4.
Pleasants  EA, Cartwright  AF, Upadhyay  UD.  Association between distance to an abortion facility and abortion or pregnancy outcome among a prospective cohort of people seeking abortion online.   JAMA Netw Open. 2022;5(5):e2212065. doi:10.1001/jamanetworkopen.2022.12065PubMedGoogle ScholarCrossref
5.
Massarweh  NN, Itani  KMF, Morris  MS.  The VA MISSION Act and the future of veterans’ access to quality health care.   JAMA. 2020;324(4):343-344. doi:10.1001/jama.2020.4505PubMedGoogle ScholarCrossref
6.
Onega  T, Duell  EJ, Shi  X, Wang  D, Demidenko  E, Goodman  D.  Geographic access to cancer care in the US.   Cancer. 2008;112(4):909-918. doi:10.1002/cncr.23229PubMedGoogle ScholarCrossref
7.
University of California San Francisco. An in-depth look at abortion facilities in the United States. Advancing New Standards in Reproductive Health. Published June 14, 2022. Accessed August 22, 2022. https://www.ansirh.org/research/research/depth-look-abortion-facilities-united-states
8.
TX SB8, 87th legislature (2021-2022). Accessed October 3, 2022. https://legiscan.com/TX/text/SB8/id/2395961
9.
 2016-2020 American Community Survey. US Census Bureau; 2021.
10.
Bearak  JM, Burke  KL, Jones  RK.  Disparities and change over time in distance women would need to travel to have an abortion in the USA: a spatial analysis.   Lancet Public Health. 2017;2(11):e493-e500. doi:10.1016/S2468-2667(17)30158-5PubMedGoogle ScholarCrossref
11.
About the topic of race. United States Census Bureau. Published March 1, 2022. Accessed October 13, 2022. https://www.census.gov/topics/population/race/about.html
12.
Weiss  DJ, Nelson  A, Gibson  HS,  et al.  A global map of travel time to cities to assess inequalities in accessibility in 2015.   Nature. 2018;553(7688):333-336. doi:10.1038/nature25181PubMedGoogle ScholarCrossref
13.
Hulland  EN, Wiens  KE, Shirude  S,  et al.  Travel time to health facilities in areas of outbreak potential: maps for guiding local preparedness and response.   BMC Med. 2019;17(1):232. doi:10.1186/s12916-019-1459-6PubMedGoogle ScholarCrossref
14.
Delamater  PL, Messina  JP, Shortridge  AM, Grady  SC.  Measuring geographic access to health care: raster and network-based methods.   Int J Health Geogr. 2012;11(1):15. doi:10.1186/1476- If 072X-11-15PubMedGoogle Scholar
15.
Apparicio  P, Abdelmajid  M, Riva  M, Shearmur  R.  Comparing alternative approaches to measuring the geographical accessibility of urban health services: distance types and aggregation-error issues.   Int J Health Geogr. 2008;7(1):7. doi:10.1186/1476-072X-7-7PubMedGoogle ScholarCrossref
16.
Lash  TL, Fox  MP, MacLehose  RF, Maldonado  G, McCandless  LC, Greenland  S.  Good practices for quantitative bias analysis.   Int J Epidemiol. 2014;43(6):1969-1985. doi:10.1093/ije/dyu149PubMedGoogle ScholarCrossref
17.
Miksanek  TJ, Edwards  ST, Weyer  G, Laiteerapong  N.  Association of time-based billing with evaluation and management revenue for outpatient visits.   JAMA Netw Open. 2022;5(8):e2229504. doi:10.1001/jamanetworkopen.2022.29504PubMedGoogle ScholarCrossref
18.
Kortsmit  K, Mandel  MG, Reeves  JA,  et al.  Abortion surveillance—United States, 2019.   MMWR Surveill Summ. 2021;70(9):1-29. doi:10.15585/mmwr.ss7009a1PubMedGoogle ScholarCrossref
19.
Dickman  SL, White  K, Grossman  D.  Affordability and access to abortion care in the United States.   JAMA Intern Med. 2021;181(9):1157-1158. doi:10.1001/jamainternmed.2021.3502PubMedGoogle ScholarCrossref
20.
Declercq  E, Zephyrin  L. Maternal Mortality in the United States: A Primer. Commonwealth Fund; 2020. Accessed August 26, 2022. https://www.commonwealthfund.org/publications/issue-brief-report/2020/dec/maternal-mortality-united-states-primer
21.
Rhodes  C, Wasserman  H.  Solving the procedural puzzles of the Texas heartbeat act and its imitators: the potential for defensive litigation.   SMU Law Rev. 2022;75(1):187.Google Scholar
Original Investigation
November 1, 2022

Estimated Travel Time and Spatial Access to Abortion Facilities in the US Before and After the Dobbs v Jackson Women’s Health Decision

Author Affiliations
  • 1Computational Epidemiology Lab, Boston Children’s Hospital, Boston, Massachusetts
  • 2Department of Epidemiology, Boston University School of Public Health, Boston, Massachusetts
  • 3Department of Obstetrics, Gynecology, and Reproductive Sciences, University of California, San Francisco
  • 4Institute for Applied Computational Science, Harvard University, Cambridge, Massachusetts
  • 5Predictive Medicine Group, Boston Children’s Hospital Computational Health Informatics Program, Boston, Massachusetts
  • 6Department of Pediatrics, Harvard Medical School, Boston, Massachusetts
  • 7Department of Epidemiology and Biostatistics, University of California, San Francisco
  • 8Bakar Computational Health Sciences Institute, University of California, San Francisco
JAMA. 2022;328(20):2041-2047. doi:10.1001/jama.2022.20424
Key Points

Question  How did travel time and spatial access to abortion facilities in the US change after the Dobbs v Jackson Women’s Health (referred to hereafter as Dobbs) Supreme Court decision?

Findings  In this repeated cross-sectional spatial analysis of 749 abortion facilities and 63 718 431 females aged 15 to 44 years in the US, estimated median and mean travel time to a facility providing an abortion in 2021 (pre-Dobbs period) were 10.9 minutes and 27.8 minutes compared with 17.0 minutes and 100.4 minutes in the post-Dobbs period, when facilities in states with total abortion bans or 6-week abortion bans were considered inactive, which was a statistically significant difference.

Meaning  In this spatial analysis, travel time to abortion facilities in the US was estimated to be significantly greater in a post-Dobbs period compared with a pre-Dobbs period.

Abstract

Importance  Abortion facility closures resulted in a substantial decrease in access to abortion care in the US.

Objectives  To investigate the changes in travel time to the nearest abortion facility after the Dobbs v Jackson Women’s Health Organization (referred to hereafter as Dobbs) US Supreme Court decision.

Design, Setting, and Participants  Repeated cross-sectional spatial analysis of travel time from each census tract in the contiguous US (n = 82 993) to the nearest abortion facility (n = 1134) listed in the Advancing New Standards in Reproductive Health database. Census tract boundaries and demographics were defined by the 2020 American Community Survey. The spatial analysis compared access during the pre-Dobbs period (January-December 2021) with the post-Dobbs period (September 2022) for the estimated 63 718 431 females aged 15 to 44 years (reproductive age for this analysis) in the US (excluding Alaska and Hawaii).

Exposures  The Dobbs ruling and subsequent state laws restricting abortion procedures. The pre-Dobbs period measured abortion access to all facilities providing abortions in 2021. Post-Dobbs abortion access was measured by simulating the closure of all facilities in the 15 states with existing total or 6-week abortion bans in effect as of September 30, 2022.

Main Outcomes and Measures  Median and mean changes in surface travel time (eg, car, public transportation) to an abortion facility in the post-Dobbs period compared with the pre-Dobbs period and the total percentage of females of reproductive age living more than 60 minutes from abortion facilities during the pre- and post-Dobbs periods.

Results  Of 1134 abortion facilities in the US (at least 1 in every state; 8 in Alaska and Hawaii excluded), 749 were considered active during the pre-Dobbs period and 671 were considered active during a simulated post-Dobbs period. Median (IQR) and mean (SD) travel times to pre-Dobbs abortion facilities were estimated to be 10.9 (4.3-32.4) and 27.8 (42.0) minutes. Travel time to abortion facilities in the post-Dobbs period significantly increased (paired sample t test P <.001) to an estimated median (IQR) of 17.0 (4.9-124.5) minutes and a mean (SD) of and 100.4 (161.5) minutes. In the post-Dobbs period, an estimated 33.3% (sensitivity interval, 32.3%-34.8%) of females of reproductive age lived in a census tract more than 60 minutes from an abortion facility compared with 14.6.% (sensitivity interval, 13.0%-16.9%) of females of reproductive age in the pre-Dobbs period.

Conclusions and Relevance  In this repeated cross-sectional spatial analysis, estimated travel time to abortion facilities in the US was significantly greater in the post-Dobbs period after accounting for the closure of abortion facilities in states with total or 6-week abortion bans compared with the pre-Dobbs period, during which all facilities providing abortions in 2021 were considered active.

Introduction

On June 24, 2022, the Supreme Court of the US delivered the Dobbs v Jackson Women’s Health Organization (hereafter referred to as Dobbs) decision, holding that there was no federal right to abortion care.1 Following Dobbs, complete or partial bans on abortion were enacted in more than 15 US states.2 Individuals seeking an abortion in these states would have to travel out of state to access abortion facilities. With 75% of those seeking abortion considered to be living on low incomes, according to 2014 estimates, this may have posed an insurmountable barrier to obtaining care.3 A 2022 study also found that greater travel requirements were associated with long delays and the inability to obtain abortions.4

The present study sought to measure overall and subgroup changes in spatial access to abortion facilities that have occurred in the post-Dobbs period.

Methods

This project was a secondary analysis of nonhuman and nonidentifiable public data and was institutional review board–exempt. Informed consent was not required. Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines for cross-sectional studies were followed.

Study Design

A repeated cross-sectional geographic analysis was conducted to estimate travel time from each census tract in the contiguous US to the nearest abortion facility. The analysis compared 2 cross-sections: pre-Dobbs (January-December 2021) and post-Dobbs (September 2022) periods. Demographics and the number of females of reproductive age (15-44 years) living more than 60 minutes from abortion care were compared in each period. A 60-minute threshold to care is consistent with government standards for access to specialty care5 and a 2022 study4 that showed that individuals living more than 50 miles from an abortion facility were more likely to still be seeking an abortion on a 4-week follow-up than those who lived closer to an abortion facility. Alaska and Hawaii were excluded from all calculations due to the unique challenges of spatial access in these states (eg, greater reliance on air travel).6

Data Sources

Abortion facility locations (n = 1134) were extracted from the Advancing New Standards in Reproductive Health database, accessed on August 18, 2022.7 All facilities in the contiguous US providing abortions in 2021 according to Advancing New Standards in Reproductive Health were included in the pre-Dobbs period. This included facilities in Texas that may have stopped performing some or all abortions in September 2021 due to Texas’ Senate Bill 8, which introduced a mechanism to prevent abortions after cardiac activity was detected.8 The post-Dobbs period was simulated by considering the facilities in the 15 states with total or 6-week abortion bans in effect as of September 30, 2022 (n = 78), as inactive for analysis (Figure 1).2 A sensitivity analysis was performed that additionally simulated all facilities in the 3 states with gestational bans between 15 and 20 weeks (n = 73) as inactive. Facilities in Alaska and Hawaii (n = 8) were excluded.

Census tract demographics for each populated census tract in the contiguous US (n = 82 993) were taken from the 2016-2020 American Community Survey (ACS), the most recently available US census data.9 Our calculations used ACS-defined female sex and ages 15 to 44 years to represent all individuals who may seek abortions. Demographic variables for stratified analyses were determined by the researchers based on previous observations of geographic, socioeconomic, and racial disparities in access to abortion services.4,10 Race and ethnicity were collected via self-identification from a closed list (“other race” option and ability to select multiple races were available) defined by the ACS and collected to meet federal and state government needs (eg, to design legislation, assess disparities).11

Spatial Analysis

Travel times from each 1-km2 grid point in the US to the nearest abortion facility were calculated using a friction surface and the Dijkstra algorithm.12,13 This method split the US into a grid of 1-km2 cells, each with a modeled burden of transversal time based on the presence of road networks, public transportation, and other factors.14 The travel time metric used here was calculated as the accumulated burden of grid-to-grid travel times if one were to follow the most efficient path from each grid point to an abortion facility. Time estimates assumed the quickest means of ground (eg, car, train) or water transportation to abortion facilities regardless of state. The travel time estimates assumed favorable conditions (eg, no traffic) and that each method of travel operated at its designed speed (eg, travelers move along a road at its speed limit).12 Travel time for each census tract was represented by the 50th percentile of all grid point travel times within the census tract. Travel time was used over distance for its flexibility measuring spatial access across urban and rural geographies, where times to travel similar distances may vary dramatically.14,15

ACS data over large regions have narrow margins of error,9,12 and the travel time computations used here were deterministic (ie, the computations estimated fixed values for travel time without error). Additionally, traditional bootstrap and simulation methods to generate travel time CIs post hoc across more than 80 000 census tracts resulted in high levels of precision (ie, margins of error <1%). To avoid overstating certainty, sensitivity intervals (SIs) were constructed reflecting sensitivity analyses employing the 2.5th (simulating faster travel) and 97.5th (simulating slower travel) travel time percentiles in place of the 50th percentile of each census tract’s grid points.16 The SI incorporated the uncertainty of where females of reproductive age may live within each census tract as well as the possibility that true travel time varies from the estimates (eg, due to traffic, driving over the speed limit).

Outcome

The primary outcomes were change in surface travel time (eg, car, public transportation) to an abortion facility and the proportion of individuals who live in a census tract that is more than 60 minutes to an abortion facility.

Statistical Analysis

Median and mean overall travel times weighted by population of females aged 15 to 44 years were computed across all census tracts. Census tract changes in travel time in the pre- and post-Dobbs periods were computed with a paired sample t test. Statistical significance was assessed at the .05 level (2-sided). Statewide changes in travel time were assessed by aggregating the median and mean of all census tracts in each state weighted by population of females aged 15 to 44 years. A secondary statewide analysis similarly assessed weighted median and mean travel time across census tracts by the presence or absence of a statewide total or 6-week abortion ban.

Stratified analyses were conducted by aggregating ACS subgroup estimates and calculating the percentage of females of reproductive age more than 60 minutes from an abortion facility in the post-Dobbs period minus the percentage of females of reproductive age more than 60 minutes from an abortion facility in the pre-Dobbs period.

The SI was treated as a 95% CI to visualize combined uncertainty in difference calculations. Because of the potential for type I error due to multiple comparisons and the non-Gaussian derivation of the SI, findings for secondary analyses should be interpreted as exploratory. Travel time calculations did not produce missingness; however, calculations were undefined or infinite in a few census tracts (eg, some islands) that were omitted (n = 101). Missingness in census data was minimal and not accessed. All analyses were conducted in R, version 3.6.2 (R Foundation).

Results

This study identified access from census tracts in the contiguous US (n = 82 892) to abortion facilities that were performing abortions in the pre-Dobbs period (n = 749) and during a simulated post-Dobbs period (n = 671) across the contiguous US. A total of 63 718 431 females of reproductive age lived in the contiguous US according to 2020 ACS estimates. In the pre-Dobbs period, there were facilities providing abortions in every state, with the most in California (n = 164) and New York (n = 87), and 6 states (Missouri, Mississippi, North Dakota, South Dakota, West Virginia, and Wyoming) with a single facility. In the post-Dobbs period, the geographic distribution only differed via simulated closures and was not otherwise assessed.

In the pre-Dobbs period, the median (IQR) estimated travel time to an abortion facility was 10.9 (4.3-32.4) minutes and the mean (SD) time was 27.8 (42.0) minutes. Also in the pre-Dobbs period, an estimated 14.6% (SI, 13.0%-16.9%) of females of reproductive age lived in a census tract more than 60 minutes from an abortion facility. In the post-Dobbs period, the estimated median (IQR) and mean (SD) travel time to an abortion facility significantly increased to 17.0 (4.9-124.5) minutes and 100.4 (161.5) minutes (paired sample t test P < .001), and an estimated 33.3% (SI, 32.3%-34.8%) of females of reproductive age lived in a census tract more than 60 minutes from an abortion facility. In a sensitivity analysis of the post-Dobbs period that considered abortion facilities in the 3 states with gestational bans between 15 and 20 weeks as inactive, an estimated 42.7% (SI, 41.9%-43.9%) of females of reproductive age lived in a census tract more than 60 minutes from an abortion facility.

There was geographic heterogeneity in increased travel time to abortion facilities (Figure 1), with the largest increases in estimated travel time in the southern region of the US, including Texas (median [IQR] increase of 493.8 [328.3-550.4] minutes and mean [SD] increase of 432.2 [172.4] minutes) and Louisiana (median [IQR] increase of 420.6 [370.9-424.4] minutes and mean [SD] increase of 420.3 [51.9] minutes). When assuming abortion facilities in the 3 states with gestational bans between 15 and 20 weeks were inactive, Louisiana became the state with the highest increase in travel time (median [IQR] increase of 591.2 [520.8-627.3] minutes and mean [SD] increase of 577.0 [54.5] minutes), followed by Texas (median [IQR] increase of 494.9 [328.3-550.4] minutes and mean [SD] increase of 432.7 [172.7] minutes).

In states with total or 6-week abortion bans, the distribution of travel times changed between the pre- and post-Dobbs period, with some census tracts experiencing greater travel time changes than others (Figure 2). States with total or 6-week abortion bans had a median (IQR) increase of 233.8 (94.6-366.1) minutes and a mean (SD) increase of 247.2 (190.6) minutes in travel time to an abortion facility compared with a median (IQR) increase of 0.0 minutes and mean (SD) increase of 0.7 (7.7) minutes in states in which they were not present.

In the pre- and post-Dobbs periods, compared with those within 60 minutes from an abortion facility, census tracts estimated to be more than 60 minutes from a facility (Table) had a higher percentage of residents without health insurance (1.8 percentage points pre-Dobbs and 4.0 percentage points post-Dobbs), a high school diploma (1.6 percentage points pre-Dobbs and 1.7 percentage points post-Dobbs), or an internet subscription (7.2 percentage points pre-Dobbs and 4.7 percentage points post-Dobbs). Census tracts more than 60 minutes from abortion facilities also had lower mean income ($8800 pre-Dobbs and $6100 post-Dobbs) than census tracts within 60 minutes to abortion facilities.

The estimated percentage of females aged 15 to 44 years living in a census tract more than 60 minutes from an abortion facility in the pre- and post-Dobbs periods varied by race and ethnicity (Figure 3). Females of Hispanic ethnicity experienced a 21.7 (SI, 20.5-23.0) percentage point increase (from 8.6% [SI, 7.8%-9.9%] to 30.3% [SI, 29.9%-31.1%]) compared with non-Hispanic females, who experienced an increase of 18.0 (SI, 15.4-20.6) percentage points (from 16.0% [SI, 14.3%-18.6%] to 33.9% [SI, 32.9%-35.7%]). American Indian or Alaska Native females had a 20.4 (SI, 15.4-25.5) percentage point increase (from 33.9% [SI, 30.3%-38.9%] to 54.4% [SI, 52.3%-57.6%]), Asian females had a 14.1 (SI, 13.8-14.5) percentage point increase (from 3.4% [SI, 3.1%-3.7%] to 17.5% [SI, 17.3%-17.8%]), Black females had a 25.6 (SI, 24.2-27.0) percentage point increase (from 10.9% [SI, 9.8%-12.4%] to 36.4% [SI, 35.9%-37.1%]), Native Hawaiian or Pacific Islander females had an 11.8 (SI, 10.7-12.8) percentage point increase (from 11.2% [SI, 10.3%-12.1%] to 23% [SI, 22.5%-23.6%]), and White females had an 18.0 (SI, 15.1-20.8) percentage point increase (from 17.1% [SI, 15.2%-19.9%] to 35% [SI, 33.8%-36.9%]).

Discussion

This study characterized changes in travel time to US abortion facilities before and after the Dobbs decision and found significantly longer travel times to abortion facilities post-Dobbs—a period modeled by assuming the closure of all abortion facilities in states with total or 6-week abortion bans—compared with pre-Dobbs—a period that included all facilities providing abortions in 2021.

Large disparities and changes in abortion facility access varied by geography. In the pre-Dobbs period, females in states that would later implement a total or 6-week abortion ban already had lower abortion facility access compared with states that did not subsequently ban abortion. In the post-Dobbs period, females in states with these bans experienced the greatest loss of facility access. This study estimated that travel time to the nearest abortion facility in the state of Texas increased by almost a full workday (common US definition of 8 hours17), highlighting the magnitude of the travel required to an abortion facility in the post-Dobbs period. Texas is a state that saw nearly 60 000 abortions per year in the pre-Dobbs period and had the highest rate of individuals without health insurance in the US.18,19

Females who were more likely to have lower incomes and be uninsured continued to have low access to abortion facilities based on this model’s estimates. Accessing an abortion facility may be prohibitive for those without the resources to travel.4 American Indian or Alaska Native, Black, and Hispanic populations experienced large absolute increases in travel time to abortion facilities. These groups have historically worse pregnancy-related mortality outcomes than nonminority populations.20

Limitations

This study has several limitations. First, it assumes that all individuals had equal access to efficient travel methods (eg, cars) and were able to navigate the legal uncertainty of seeking care across state borders. Second, air travel, which may be more appropriate over long distances, was not modeled. Third, the model only characterized spatial accessibility, one of many potential barriers to accessing care.15 Fourth, the results relied on the Advancing New Standards in Reproductive Health database, for which updates are annual and may not reflect real-time status due to the rapidly changing abortion landscape and the manual verification of facilities’ operational status. This limitation was mitigated by simulating closures based on updated legal status of abortion by state. There may also be nonadvertising facilities providing abortions (eg, hospitals or primary care clinicians) that were not included in the database; however, these locations are unlikely to be operating in states with abortion bans. Fifth, individual states with abortion bans may bypass spatial barriers by mail-ordering medication, minimizing the effect of the present findings. However, this requires legal risk and internet access, the latter of which is lacking in many households that are more than 60 minutes from abortion facilities. Sixth, across 2021 and 2022 there was substantial and dynamic complexity in gestational bans and abortion laws throughout court systems that a static model cannot fully capture. For example, Senate Bill 8 in Texas limited abortions by a biological cutoff; however, its enforcement capability was still unresolved when the Dobbs decision was issued.21 Therefore, Texas facilities performing abortions in 2021 were included in the pre-Dobbs model. Additionally, the presented post-Dobbs model conservatively included 3 states with abortion bans between 15 and 20 weeks’ gestation, because most abortions occur prior,18 and assumed that abortion facilities in the 9 states with court-blocked bans2 (eg, Indiana) were currently operating. If these cases are resolved to further limit abortions, the post-Dobbs travel time calculations presented here will be underestimates.

Conclusions

In this repeated cross-sectional spatial analysis, estimated travel time to abortion facilities in the US was significantly greater in the post-Dobbs period after accounting for the closure of abortion facilities in states with total or 6-week abortion bans in effect compared with the pre-Dobbs period, during which all facilities providing abortions in 2021 were considered active.

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Article Information

Corresponding Author: Yulin Hswen, ScD, University of California, San Francisco, 490 Illinois St, San Francisco, CA 94158 (yulin.hswen@ucsf.edu).

Accepted for Publication: October 17, 2022.

Published Online: November 1, 2022. doi:10.1001/jama.2022.20424

Author Contributions: Mr Rader had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Drs Brownstein and Hswen are co−senior authors.

Concept and design: All authors.

Acquisition, analysis, or interpretation of data: Rader, Upadhyay, Sehgal, Hswen.

Drafting of the manuscript: Rader, Sehgal, Reis, Hswen.

Critical revision of the manuscript for important intellectual content: Rader, Upadhyay, Sehgal, Brownstein, Hswen.

Statistical analysis: Rader.

Administrative, technical, or material support: Rader, Upadhyay, Sehgal.

Supervision: Reis, Brownstein, Hswen.

Conflict of Interest Disclosures: None reported.

Funding/Support: Dr Upadhyay acknowledges funding from the BaSe Family Fund, the Lisa and Douglas Goldman Fund, the Preston-Werner Foundation, and the Isabel Allende Foundation. The other authors did not receive funding for this work.

Role of the Funder/Sponsor: The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Additional Contributions: The authors thank Rohan Khazanchi, MD (Harvard Internal Medicine-Pediatrics Residency Program); Katelynn O’Brien, BS (Boston Children’s Hospital); and Kathryn Cordiano, MPH (Boston Children’s Hospital), for their assistance. These individuals did not receive compensation for their contributions.

References
1.
Dobbs v Jackson Women’s Health Organization_ US _ (June 24, 2022). Accessed October 25, 2022. https://www.supremecourt.gov/opinions/21pdf/19-1392_6j37.pdf
2.
McCann  A, Walker  AS, Sasani  A, Johnston  T, Buchanan  L, Huang  J. Tracking the states where abortion is now banned. New York Times. Updated September 30, 2022. Accessed October 13, 2022. https://www.nytimes.com/interactive/2022/us/abortion-laws-roe-v-wade.html
3.
Jerman  J, Jones  RK, Onda  T. Characteristics of US abortion patients in 2014 and changes since 2008. Guttmacher Institute. May 2016. Accessed October 24, 2022. https://www.guttmacher.org/report/characteristics-us-abortion-patients-2014
4.
Pleasants  EA, Cartwright  AF, Upadhyay  UD.  Association between distance to an abortion facility and abortion or pregnancy outcome among a prospective cohort of people seeking abortion online.   JAMA Netw Open. 2022;5(5):e2212065. doi:10.1001/jamanetworkopen.2022.12065PubMedGoogle ScholarCrossref
5.
Massarweh  NN, Itani  KMF, Morris  MS.  The VA MISSION Act and the future of veterans’ access to quality health care.   JAMA. 2020;324(4):343-344. doi:10.1001/jama.2020.4505PubMedGoogle ScholarCrossref
6.
Onega  T, Duell  EJ, Shi  X, Wang  D, Demidenko  E, Goodman  D.  Geographic access to cancer care in the US.   Cancer. 2008;112(4):909-918. doi:10.1002/cncr.23229PubMedGoogle ScholarCrossref
7.
University of California San Francisco. An in-depth look at abortion facilities in the United States. Advancing New Standards in Reproductive Health. Published June 14, 2022. Accessed August 22, 2022. https://www.ansirh.org/research/research/depth-look-abortion-facilities-united-states
8.
TX SB8, 87th legislature (2021-2022). Accessed October 3, 2022. https://legiscan.com/TX/text/SB8/id/2395961
9.
 2016-2020 American Community Survey. US Census Bureau; 2021.
10.
Bearak  JM, Burke  KL, Jones  RK.  Disparities and change over time in distance women would need to travel to have an abortion in the USA: a spatial analysis.   Lancet Public Health. 2017;2(11):e493-e500. doi:10.1016/S2468-2667(17)30158-5PubMedGoogle ScholarCrossref
11.
About the topic of race. United States Census Bureau. Published March 1, 2022. Accessed October 13, 2022. https://www.census.gov/topics/population/race/about.html
12.
Weiss  DJ, Nelson  A, Gibson  HS,  et al.  A global map of travel time to cities to assess inequalities in accessibility in 2015.   Nature. 2018;553(7688):333-336. doi:10.1038/nature25181PubMedGoogle ScholarCrossref
13.
Hulland  EN, Wiens  KE, Shirude  S,  et al.  Travel time to health facilities in areas of outbreak potential: maps for guiding local preparedness and response.   BMC Med. 2019;17(1):232. doi:10.1186/s12916-019-1459-6PubMedGoogle ScholarCrossref
14.
Delamater  PL, Messina  JP, Shortridge  AM, Grady  SC.  Measuring geographic access to health care: raster and network-based methods.   Int J Health Geogr. 2012;11(1):15. doi:10.1186/1476- If 072X-11-15PubMedGoogle Scholar
15.
Apparicio  P, Abdelmajid  M, Riva  M, Shearmur  R.  Comparing alternative approaches to measuring the geographical accessibility of urban health services: distance types and aggregation-error issues.   Int J Health Geogr. 2008;7(1):7. doi:10.1186/1476-072X-7-7PubMedGoogle ScholarCrossref
16.
Lash  TL, Fox  MP, MacLehose  RF, Maldonado  G, McCandless  LC, Greenland  S.  Good practices for quantitative bias analysis.   Int J Epidemiol. 2014;43(6):1969-1985. doi:10.1093/ije/dyu149PubMedGoogle ScholarCrossref
17.
Miksanek  TJ, Edwards  ST, Weyer  G, Laiteerapong  N.  Association of time-based billing with evaluation and management revenue for outpatient visits.   JAMA Netw Open. 2022;5(8):e2229504. doi:10.1001/jamanetworkopen.2022.29504PubMedGoogle ScholarCrossref
18.
Kortsmit  K, Mandel  MG, Reeves  JA,  et al.  Abortion surveillance—United States, 2019.   MMWR Surveill Summ. 2021;70(9):1-29. doi:10.15585/mmwr.ss7009a1PubMedGoogle ScholarCrossref
19.
Dickman  SL, White  K, Grossman  D.  Affordability and access to abortion care in the United States.   JAMA Intern Med. 2021;181(9):1157-1158. doi:10.1001/jamainternmed.2021.3502PubMedGoogle ScholarCrossref
20.
Declercq  E, Zephyrin  L. Maternal Mortality in the United States: A Primer. Commonwealth Fund; 2020. Accessed August 26, 2022. https://www.commonwealthfund.org/publications/issue-brief-report/2020/dec/maternal-mortality-united-states-primer
21.
Rhodes  C, Wasserman  H.  Solving the procedural puzzles of the Texas heartbeat act and its imitators: the potential for defensive litigation.   SMU Law Rev. 2022;75(1):187.Google Scholar
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