Understanding How Supreme Court Decisions Impact Health

United States Supreme Court Building in Washington, D.C.

Several major court decisions in recent months — related to affirmative action in university admissions, reproductive rights, right to refuse service, transgender and gender-affirming health, and others issues — are likely to have profound implications for health and racial equity. Evaluating the effects of these decisions and how differences in local responses moderate the public health consequences is a high priority. Such evaluations may lead to successful reduction of potential harms and identification of responsive interventions that advance both health and racial equity. Yet, rigorous evaluation of court decisions will be difficult due to data availability, methodologic issues, and data retention amidst changing policy contexts, among many potential challenges. In this post, we lay out major research challenges and possible approaches in delivering convincing evidence on the health effects of these decisions.


Methodological Challenges 

Major methodological challenges arise for Supreme Court decisions, because they directly impact the ways in which federal policies are implemented and ultimately affect all US residents. This eliminates opportunities to exploit geographic variation in the policy to estimate health effects. Valid inference is also challenging when the timing of social policies are co-occurring, as it will be difficult to disentangle the independent effects of prohibiting affirmative action in college admissions, reproductive rights, or equal access to services and health care. 

Additional methodological challenges relate to the mechanisms by which court decisions influence health, and the time delay before health impacts are evident. After previous statewide affirmative action bans, the number of Black, Hispanic, and Indigenous persons completing a STEM degree dropped after 5 years. Because higher education positions graduates for advanced professional roles, such restrictive policies may contribute to inadequate representation of health care and service providers and future leaders in other fields. These consequences may emerge over years or decades.     


Possible Approaches

Capturing real-time data on local and institutional policy changes resulting from federal court decisions will be essential to evaluate the effects of local responses. For example, impact evaluations of current investments in states with previously enacted affirmative action bans can inform best practices for institutional and statewide interventions. Further, evaluation of the mechanisms in which policy changes are impacting the lives of those affected can help understand overall health effects and provide needed evidence to guide the actions of advocates, practitioners, and decision-makers. This will likely include both quantitative mediation models and qualitative work to provide richer understanding of how people change their behaviors and expectations in the wake of the court decisions.

Given existing inequities, it is most likely that certain social groups will be disproportionately harmed by policy changes. Pre-specifying theory-driven research hypotheses and testing for heterogeneous treatment effects can strengthen the impact of findings and allow detection of the compounding burden of hostile policy contexts across intersectionalities of race, ethnicity, gender identity, socioeconomic position, sexual orientation, among others. One way to identify and evaluate effects specific to these impacted groups is to establish the effects of the policies using difference-in-difference or triple-difference methods. 


Putting Evidence into Action

Local and institutional responses to federal court decisions are likely to be heterogeneous and dynamic. For example, many universities across the US have responded to the affirmative action ban by publicly affirming the value they place on diversity: these statements may (or may not) offset the chilling effect on applications and expectations documented in some prior work. Universities will implement the removal of affirmative action decisions in admissions in various ways. Capturing these differences will highlight effective responses that are focused on health and racial equity and can inform new policies and institutional practices.

Prior E4A-funded research demonstrated that state level anti-affirmative action decisions increase certain risky health behaviors, including substance use and smoking. The mechanisms of this were not directly due to adverse admissions decisions, but mental health consequences of anticipated admissions decisions and discriminatory campus environments such as psychological distress and depression. The dissemination of this and other research evidence into spaces beyond the academy may help to create change in systems that can inform critical anti-racist policies for combating adverse effects of affirmative action bans. 

Current research on abortion access - including work from the Turnaway Study - demonstrated that people who have been refused abortions have greater initial adverse mental health outcomes but over time had similar mental health outcomes with people who had an abortion. Further, high levels of perceived abortion stigma emerged for years afterwards, in particular for those who were denied an abortion initially and who later got an abortion elsewhere or miscarried. Research highlighting heterogeneous long-term health trajectories and the complexities in unintended health consequences provide evidence to disprove overarching policies that restrict women’s access to abortion solely on the false basis that abortion harms women’s mental health.



The changes enacted by recent, and potentially in forthcoming, court decisions may have profound and long-lasting health consequences for the country. Population health researchers, in concert with policymakers and community leaders, will need to tackle myriad new questions about how the policies and various responses to those policies influence health and racial equity. Methodological rigor, innovation, and inclusion of the people directly affected by these decisions will be essential to provide an accurate understanding of those consequences.  


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About the author(s)

Ye Ji Kim, PhD, is a Postdoctoral Fellow in the E4A Methods Lab and is a frequent contributor to the E4A blog. 

M. Maria Glymour, ScD, MS, is an Associate Director of E4A and runs the E4A Methods Lab. 

Marilyn Thomas, PhD, MPH, is a Postdoctoral Fellow at the University of California, San Francisco. 

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