Health disparities along racial and socioeconomic lines are a persistent challenge for policymakers and researchers looking to improve health outcomes. The COVID-19 pandemic has highlighted and at least temporarily exacerbated these patterns: one estimate indicates that despite comprising only 13% of the U.S. population, non-Hispanic Black people accounted for 34% of COVID-related deaths. The causes driving these vastly different outcomes are numerous, often generational in timescale, sometimes inter-related, and geographically dependent, all of which make effective research and policy responses difficult.
A new book from the National Institutes of Health (NIH) seeks to provide policymakers and researchers tools to close the gap with bold, novel approaches. One such approach is a rapidly advancing and interdisciplinary research framework broadly referred to as complex systems science. This framework is uniquely equipped to grapple with the inherent complexity of health disparities and, as our previous work has shown, other policy research areas concerned with progress toward social justice.
Moving past isolating individual factors
The ultimate goal of health disparities research should be to uncover key drivers and craft policies and practices that can effectively and sustainably address them. Until recently, a challenge in reaching this goal has come from reliance on methods focused on isolating and separately quantifying the contribution of individual factors.
The impact of such analyses is limited in two ways. First, the data necessary to convincingly estimate the effects of individual factors is difficult to find or collect (especially in small populations). Second, and more fundamentally, even when efforts to quantify the contribution of individual drivers of health disparities are successful, they are limited in their ability to contribute to meaningful, sustainable solutions because health disparities are caused by multiple, overlapping factors that often operate on large time scales (i.e. across generations) and differ substantially across individuals and settings. Taking a broad perspective that acknowledges and explicitly grapples with this complexity is the best way to effect positive change.
Embracing complexity in health disparities
Complex systems science provides a way forward in addressing health disparities research, policy, and practice. Researchers and policymakers can use complex systems approaches to explore interacting mechanisms and answer new kinds of questions concerning why observed levels of health disparities occur, which effect pathways or leverage points might matter most, why past or existing policies and interventions have observed effects in a given context, and how novel proposed policies or interventions might affect different communities (including heterogeneous effects and unintended negative consequences). In short, we can address questions about what works, for whom, and why.
For example, our research has shown that observed physical activity patterns are generated by a combination of individual, social, and environmental factors. People’s exercise behaviors are inextricably intertwined: they are more likely to engage in these activities when others do as well because of additional opportunities (e.g. the presence of casual ball games or running groups), social influence (e.g. following the example of friends and family), and collective effects on the built environment (e.g. demand for safe bike lanes in a community). Strategies that explicitly incorporate this insight can be much more effective than ones that concentrate solely on individual-level factors such as information and motivation.
To achieve this wide-angle perspective, complex systems science incorporates a variety of emerging research tools and techniques, including both qualitative and quantitative methodology (and synergistic combinations of both). In our chapter of the NIH publication, we provide an overview of when and how to use these approaches, highlighting topics such as the importance of selecting methods that are appropriate for specific research goals, the role of theory and data, assembling an effective research team, and communicating findings to policymakers and other stakeholders.
Beyond health, towards social justice
Beyond providing a point of entry for researchers and policymakers unfamiliar with complex systems science, this work contributes to a broader conversation that is occurring among economists and other social scientists around research methodology that promotes social justice. The economic and social upheavals caused by the COVID-19 pandemic, coupled with high-profile incidents of police violence inflicted upon Black people, have made it starkly clear that there is both need and appetite for systemic reform. In the best tradition of science, many economists have committed themselves to finding ways to help with this endeavor. Alongside commendable efforts to study the potential impact of large-scale changes in policy and practice, the field is also beginning to revisit long-standing conventions about theories, assumptions, and methods that can affect our ability to understand and address the structures that perpetuate inequalities.
Over the past several years, we have demonstrated the promising role that complex systems science can play in advancing this goal. For example, we have been able to compare how different policy approaches to tobacco retail control might affect disparities in smoking across different racial and socioeconomic groups across settings. We have considered the possible effects of different college tuition subsidy programs (sometimes called “free college”) on equitable access to higher education. We have provided rapid-response public health guidance on effectively and equitably responding to the COVID-19 pandemic. In forthcoming work on exposure to HIV transmission, we argue that working across policy areas—specifically, coupling judicial reform with public health interventions—is a promising way to reduce pervasive disparities. And finally, we explore ways in which complex systems science can productively be applied to tackle large-scale, deeply entrenched problems affecting billions of people worldwide by considering the dynamic intersection between obesity, undernutrition, and climate change.
The way forward for researchers and policymakers seeking to reduce health disparities and ultimately move toward a more just society has historically been confounded by complexity. Perspectives and tools derived from complex systems science can reveal new avenues for substantive progress.