Research ArticleOriginal Research

Fewer Abortions in States with More Family Physicians

Amanda Weidner
The Journal of the American Board of Family Medicine September 2026, 39 (1) 167594; DOI: https://doi.org/10.3122/jabfm.2025.250295R1

Abstract

Purpose Primary care physicians providing abortion services—particularly family physicians (FPs), who provide the majority of care in rural and underserved settings—could enhance access to abortion and family planning services. The primary objective of this study was to evaluate the association between the rate of abortions and availability of FPs by state.

Methods This was an exploratory ecological study of secondary data compiled from several state sources in the United States. The primary dependent variable was abortion rate, and the primary independent variable was FPs per population, with internists and obstetrician/gynecologists (ob/gyns) analyzed as comparison. Other variables included pregnancies and abortion clinics per population; percent of a state’s population in rural areas; and state abortion law. Each comparison was analyzed with a two-tailed Pearson’s correlation test followed by multivariate linear regression.

Results The number of physicians per 100,000 population was significant in all three models when controlling for the other variables, but in different directions: more internists and more ob/gyns were associated with greater abortion rates (B = .253 [.037], P < .001 and B = .807 [.174], P < .001), while more FPs were associated with lower abortion rates (B = -.212 [.064], P = .002). Each model was reliably predictive of abortion rates and explained most of the variance in abortion rates by state.

Conclusions Fewer abortions in states with more FPs and more in states with ob/gyns and internists may suggest an access issue in the states with more FPs. FPs providing abortion care could be part of a solution for improving patient access to that care, particularly in rural areas.

Introduction

Ongoing access issues for elective abortion (referred to as “abortion” throughout the remainder of the manuscript) in the United States were made worse following the US Supreme Court decision in Dobbs v Jackson Women’s Health.1 Since the decision in 2022, access, particularly in rural and underserved communities, has declined and barriers to care have increased, as many states have banned abortion altogether, changed the laws on allowable gestation, and added Targeted Regulations of Abortion Providers (TRAP) laws to restrict where and how abortion services can be provided and who can provide them.2–7

One avenue to improve access to abortion services, where they remain legal, is to offer them within primary care settings; this is particularly important now when medication abortion is easier to access and funding threats are impacting care at abortion clinics.8–11 Many patients would prefer to get abortion services from their primary care clinican12 and believe they can access this care in their primary care offices13; this is well within the scope for primary care clinicians.9,10 There have been ongoing and recent calls for both general internists and family physicians to offer abortion care,9,14–17 though abortion training is not required in either specialty. With the decline of internists serving as primary care physicians,18 family physicians provide the majority of primary care services in rural and underserved communities.19–21 Some family medicine residents are eager to be trained in abortion care,16 and 11% report being trained in residency.22 However, only 3%-4% of family physicians report actually providing abortion care in their practice setting.22–24

Thus, increasing abortion care from family physicians in primary care settings could increase abortion access for a greater breadth of the population. However, despite this theoretical implication, no population-level exploration of abortion and family physicians or other clinicians exists in the literature. Thus, it is hard to know the depth or breadth of the opportunity to affect abortion access.

As such, the primary objective of this study was to evaluate whether there is any association between the rate of abortions and availability of family physicians, with internists and obstetrician/gynecologists (ob/gyns) as comparison. The secondary objective was to evaluate whether these relationships are modified by the rurality of the state, or modified by the attitude toward abortion in that state, using current abortion law as proxy.

Methods

This study was an exploratory ecological study using secondary data from multiple sources. Data were explored at the state level, including all 50 states and Washington, DC, as the smallest available unit of aggregation for all variables. The main dependent variable was elective abortion rate, defined as the number of abortions per 1000 women of reproductive age, which includes women from ages 15 to 44. Abortion rate, as well as total number of abortions, pregnancy rate (number of pregnancies per 1000 women ages 15 to 44), total number of pregnancies, and population of reproductive age women (ages 15-44) were taken from the Guttmacher Institute’s report on pregnancies, births, and abortions in the United States from 1973-2020; this study used the 2020 data as the most recent data.25

The main independent variables were number of physicians in direct patient care per 100,000 population, specifically family physicians, internists, and ob/gyns. Physician workforce data was from 2022 counts; earlier data by state and specialty were not publicly available. These data were from the Association of American Medical Colleges US Physician Workforce Data Dashboard, which aggregated data by specialty from the American Medical Association’s Physician Professional Data.26 The counts of internists and family physicians did not specify who is working in primary care settings as distinct from other settings, such as inpatient, though the grouping methodology should exclude those who have sub-specialized (eg, critical care, hospice and palliative care, geriatrics).27 Other variables included the number of brick-and-mortar abortion clinics (as of 2020, from another Guttmacher report)28; percent of the state’s population living in rural areas based on the 2020 US Census29; and the current law on abortion in the state in December 2024 from Kaiser Family Foundation’s (KFF) Dashboard on the Status of Abortion Bans in the United States.5 The specific variables and their data sources, including links for direct access, are shared as a supplemental appendix.

The population and dependent variables used 2020 data, but the abortion law data was based on current status as of December 2024, post-Dobbs. It was included as a proxy for attitudes toward abortion, including prior legal restrictions, in a given state before the Dobbs decision. The KFF tracker had 5 categories: complete abortion ban; gestational limit between 6 and 12 weeks since last menstrual period (LMP); gestational limit between 18 and 22 weeks LMP; gestational limit at or near viability; and no gestational limits. At the time data were gathered, no states had laws banning abortion after gestational ages between 12 and 18 weeks. I collapsed the higher gestational limits (> 18 weeks LMP) into one category to create 3 categories for analysis, to better capture the acceptability of abortion services in the state: restrictive of abortion (abortion banned), permissive of abortion (abortion allowed > 18 weeks LMP), and somewhere in between (abortion allowed between 6 and 12 weeks LMP).

Two states (Missouri and North Dakota) had legislatures that passed an abortion ban that was struck down by the courts in the fall of 2024, so as of December 2024 they were in the “gestational limit at or near viability” group while the bans work through the court system. Since I am using this variable as proxy for climate around abortion in a state, and both states had laws passed to ban abortions, I recategorized both states to “abortion banned” for this analysis.

After assessing normality of data within each variable, I conducted exploratory bivariate analysis using scatter plots, then used two-tailed Pearson correlation for bivariate statistical analysis before constructing a multivariate linear regression model. An alpha level of P = 0.05 was used to assess statistical significance. All variables in the dataset except state and current law on abortion in the state were continuous variables; dummy variables for the current law variable were created for use in linear regression modeling. All statistical analysis was conducted in SPSS 28.0.0.0 and exploratory visual modeling was conducted using Tableau Desktop 2022.3. As this study used publicly available aggregated data, it did not meet the criteria for IRB review of human subjects research.

Results

The total sample size for analysis was 51, all 50 states and Washington, DC. In bivariate analysis, there were significantly lower rates of abortion in states with more family physicians (r = -.541, P < .001), but significantly higher rates of abortion in states with more internists (r = .668, P < .001) and in states with more ob/gyns (r = .607, P < .001). There were also significantly lower rates of pregnancy (r = -.385, P = .005) and significantly higher numbers of women per abortion clinic (ie, fewer clinics per population; r = .331, P = .018) in states with more family physicians, but no correlation with the number of internists or ob/gyns. These relationships are shown in Figure 1.

Associations Between Physician Workforce Composition and State-Level Reproductive Health Indicators Notes: Bivariate analyses of 50 US states and Washington, DC, examining associations between the number of family physicians, internists, and obstetrician-gynecologists in direct patient care (per 100,000 population, 2022, AAMC US Physician Workforce Data Dashboard) and state-level reproductive health indicators. Indicators include abortion and pregnancy rates (per 1,000 women ages 15-44) and the number of women per abortion clinic (1,000 women ages 15-44 per clinic), based on 2020-2024 publicly available data. Each point represents a state; lines indicate the direction and strength of correlation for each physician group.
Figure 1. Associations Between Physician Workforce Composition and State-Level Reproductive Health Indicators

Notes: Bivariate analyses of 50 US states and Washington, DC, examining associations between the number of family physicians, internists, and obstetrician-gynecologists in direct patient care (per 100,000 population, 2022, AAMC US Physician Workforce Data Dashboard) and state-level reproductive health indicators. Indicators include abortion and pregnancy rates (per 1,000 women ages 15-44) and the number of women per abortion clinic (1,000 women ages 15-44 per clinic), based on 2020-2024 publicly available data. Each point represents a state; lines indicate the direction and strength of correlation for each physician group.

Significantly more family physicians per population were in states with greater percentages of the population in rural areas (r = .578, P < .001); the opposite was true for internists (r = -.453, P < .001) and ob/gyns (r = -.363, P = .009). There were also significantly fewer pregnancies (r = -.381, P = .006), fewer abortions (r = -.604, P < .001) and more women per abortion clinic (ie, fewer clinics per population; r = .344, P = .013) in more rural states. Current state law about abortion was not statistically correlated with number of family physicians per population, though there are more internists and ob/gyns in states with laws allowing abortions > 18 weeks LMP (r = .463, P < .001 and r = .384, P = .005, respectively) and fewer in states with abortion bans (r = -.389, P = .005 and r = -.315, P = .024, respectively). States with abortion bans are significantly more likely to have a greater rural population (r = .423, P = .002) and those with laws allowing abortion > 18 weeks are correlated with a smaller rural population (r = -.391, P = .005). Complete results of the bivariate analysis are included in Table 1.

View this table:
Table 1. Bivariate Correlations Among Physician Workforce, Reproductive Health Indicators, and State Contextual Factors Across 50 US States and Washington, DC (2020-2024 Publicly Available Data; Two-Tailed Pearson’s Correlation)

In multivariate regression (complete results presented in Table 2), each of the three models looking at the abortion rate and number of family physicians (F = 14.674), internists (F = 28.4958), or ob/gyns (F = 19.2125) per 100,000 population were statistically significant (all P < .001), and thus reliably predictive of abortion rates. Most of the variance in abortion rates were explained by the models (R2 = .668 or 66.8% of variance for the family physician model; R2 = .798 or 79.8% of the variance for the internist model; R2 = .723 or 72.3% of the variance for the ob/gyn model). Since number of abortions is dependent on number of pregnancies, in all three models, the pregnancy rate was significantly associated with a higher abortion rate (all P < .001). Additionally, in all three models, states with current abortion bans had significantly lower rates of abortion in 2020 than those with laws allowing abortion > 18weeks LMP (B = -6.582 [1.459], P < .001 for family physicians; B = -2.929 [1.106], P = .011 for internists; B = -3.443 [1.289], P = .011 for ob/gyns).

View this table:
Table 2. Multivariate Linear Regression Models of Physician Workforce and Abortion Rates Across 50 US States and Washington, DC (2020-2024 Publicly Available Data)

The relationship for the main independent variable in the model, physicians per 100,000 population, was also significant in each model when controlling for the other variables, but in different directions: more internists and more ob/gyns were significantly associated with greater abortion rates (B = .253 [.037], P < .001 and B = .807 [.174], P < .001), while more family physicians were significantly associated with lower abortion rates (B = -.212 [.064], P = .002). In other words, adding one family physician per 100,000 people is associated with about 0.22 fewer abortions per 1,000 women of reproductive age, while adding one internist per 100,000 is associated with 0.25 more abortions per 1,000 women, and one additional ob/gyn is associated with 0.85 more abortions per 1,000 women.

Discussion

The findings of this ecological study demonstrate that even when controlling for rurality of population and climate around abortion in a state (using the 2024 law as proxy), states where there are more family physicians have a significantly lower rate of abortions. While this could be due to other variables not included in the model, such as patient demographics (eg, older patient populations), there may be other reasons that explain this relationship, and these warrant further exploration. For example, patients in states with more family physicians and fewer abortion clinics may not see their family physician as a possible source of access for abortion services and may go outside of the state for care. As laws around abortion continue to evolve, family physicians may be reticent to wade into abortion care; their fear of stigma and legal repercussions may prevent them from discussing or offering abortion care, again requiring patients to go elsewhere. Alternatively, given that comprehensive care is a pillar of the discipline, and that there is a significant negative correlation between the number of family physicians and pregnancy rates in bivariate analysis, the lower abortion rates could suggest that patients cared for by FPs are getting better access to contraceptive care.

Somewhat surprisingly, considering that brick-and-mortar abortion clinics provide more than 80% of clinician-provided abortions,28 the number of abortion clinics is not a significant predictor of abortion rates when controlling for other variables in these models. Also surprisingly, the number of abortion clinics was not correlated with the state’s climate around abortion; in other words, restrictive states did not have fewer clinics per population than permissive states.

With this in mind, and in consideration of overall access to abortion services, there were significantly higher rates of abortions in states where there are more internists and ob/gyns when controlling for the other variables. This might suggest adding more of these physician types could help support access; however, this may instead perpetuate current access gaps. For example, there were significantly more internists and ob/gyns in states more permissive of abortion and fewer in restrictive states; there were also significantly fewer in states with a greater percentage of their population living in rural areas. Clearly, in states that have a complete abortion ban, adding additional clinicians will not increase access. However, for states where abortion is still legal, particularly rural states where there are significantly more family physicians per population and significantly fewer abortion clinics per woman, family physicians could be a key part of the abortion access solution.

In this study I used the late-2024 abortion laws in a state as a proxy for the climate of a state around abortion in recent years, including any prior laws impacting patient access. The data support this proxy variable: Abortion rates in 2020 were significantly lower in states that had complete abortion bans in 2024. A limitation of the study, however, was using data from different years. Data on physician workforce numbers were not available for the year 2020; the earliest available data were for 2022, so the physician numbers are not a perfect match for the 2020 pregnancy, abortion, and abortion clinic numbers. Given the size of the sample and the slow increase of physician workforce over time, this should at least suggest that directionality of the associations would not change, though the magnitude of them may. Additionally, there are other limitations with using the 2020 data in this study; in particular, some of the data are pre-COVID and before the reversal of Roe v Wade, and since then there have been many changes in clinician-practice patterns. For example, in Idaho, in the first 15 months after the overturning of Roe v Wade, and a subsequent statewide abortion ban, nearly a quarter of ob/gyns left the state.30 The 2022 physician data are still early enough to not capture the full impacts of these transitions in practice; repeating this study with post-Dobbs data when they become available would be worthwhile. These data focused on physicians, though increasing numbers of advanced practice providers and other clinicians providing abortion are also an important factor in addressing access.31

The greatest limitation in this study is the use of secondary data, so the model cannot include all variables that we know impact the relationships under study. In addition, using data aggregated at the state level, when we know practice and healthcare patterns are often better examined at a county or community level is another limitation. For example, using the percentage of a state whose population lives in a rural area is not the same as looking more closely at access and care in those rural places. Despite these limitations, this exploratory ecological study has added a population-level view of the relationships between abortion rates and family physicians, as well as internists and ob/gyns, to begin to add more context about the opportunity for family medicine to have an effect on abortion access in the communities they care for. Future studies could explore these relationships at more granular levels. Additional data on the family physicians who currently provide abortions would be useful for considering how to better expand this scope of service for others—for example, it would be useful to know if they are providing medication or procedural abortions or both; do they provide them in primary care office settings, in abortion clinics, both, or somewhere else altogether? Particularly with the recent changes that have made medication abortion easier to access, increasing the number of family physicians who provide abortions could support increased access for patients and communities, especially in rural and underserved communities.

Conflicts of Interest

None.

Corresponding Author

Amanda Weidner, MPH, Department of Family Medicine, University of Washington, Seattle, WA, aweidner{at}uw.edu

This article was externally peer reviewed.

Acknowledgements

I would like to thank my incredible colleagues Anastasia Coutinho, MD, MPH, Grace Shih, MD, MAS, and Tiosha Bailey, DrPH, for their review and feedback on earlier versions of this manuscript.

Appendix

View this table:
Appendix Table 1. Measurement/Variables Table (Data Dictionary)
  • Received for publication July 31, 2025.
  • Accepted for publication November 17, 2025.

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