Diversions: How the Underrepresentation of Research on Advantaged Groups Leaves Explanations for Health Inequalities Incomplete

This study argues that health inequalities research systematically overlooks the role that racially and socioeconomically privileged groups play in producing health disparities and documents this “diversion” across grants, datasets, published articles, and national health policy.

Introduction

This study examines a significant blind spot in health inequalities research: the near-total absence of scrutiny directed toward racially and socioeconomically advantaged groups. The authors introduce the concept of “health-inequality diversions”, a pattern in which research ignores, downplays, or excuses the inequality-generating behaviors of advantaged people while focusing almost exclusively on the characteristics, behaviors, and circumstances of disadvantaged groups. The authors argue that this imbalance produces incomplete scientific explanations, misdirects policy interventions, and ultimately allows health inequalities to persist.

This study is important because it directly challenges the dominant framing of health disparities research, which tends to ask, “What is wrong with or different about disadvantaged populations?” rather than “What are advantaged groups doing to maintain and extend their advantage?” By naming and empirically documenting this pattern, the authors provide a framework for identifying and addressing a structural bias within the research process itself.

Bruce G. Link is a Distinguished Professor of Public Policy and Sociology at the University of California, Riverside, and co-developer of Fundamental Cause Theory, a cornerstone framework in medical sociology. San Juanita García is an Assistant Professor of Chicana and Chicano Studies at University of California, Santa Barbara, whose research focuses on immigration, Latinx health, and intersectionality. Their combined expertise in sociological theory, health inequalities, and racialization directly informs this study and its analysis.

Methods and Findings

To identify evidence of health-inequality diversions, the authors conducted a systematic content analysis across four key stages of the research production process: NIH R01 grants, major health datasets, published research articles, and national policy documents. At each stage, they assessed whether existing research examined the inequality-generating actions of advantaged groups directly, indirectly (through disadvantaged groups’ reports of discrimination or exploitation), or instead located the “problem” in the disadvantaged populations.

1. National Institute of Health (NIH) R01 Grants (2015 to 2019): R01 is the NIH’s standard, most common grant mechanism for funding investigator-initiated research. The authors reviewed 349 R01 grants using terms like “health disparities” or “health inequities” .
   •  No grants directly examined the health-inequality-generating behaviors of advantaged groups.
   • Only 18.3% mentioned discrimination, stigma, or related concepts.
   • 70.8% emphasized health behaviors, biomarkers, or genetic/epigenetic factors within disadvantaged populations.
2. Major Health Datasets (7 datasets): The authors reviewed seven widely used health datasets:the National Longitudinal Study of Adolescent to Adult Health (Add Health), the Midlife in the United States Study (MIDUS), the American’s Changing Lives Survey (ACLS), the Health and Retirement Study (HRS), the National Health Interview Survey (NHIS), the National Health and Nutrition Examination Survey (NHANES), and the Behavioral Risk Factor Surveillance System (BRFSS)
   • None of these major health datasets  included repeated measures of advantaged groups’ behaviors (e.g., using social connections for better care, exclusionary intent).
   • None included racial discrimination as a core repeated measure. When measures of racial discrimination were included, they were generally sparse and were often added only after longitudinal studies had already been underway for several years.  
   • In contrast, all datasets contained extensive measures of individual-level health behaviors, biomarkers, traits, and genetic data for disadvantaged groups.
3. Published Research Articles: The authors reviewed 324 articles published in leading journals, including the American Journal of Public Health (AJPH), the Journal of Health and Social Behavior (JHSB), and SSM–Population Health (SSM-PH).
   • Only 2.2% of articles directly examined the role of advantaged groups in producing health inequalities.
   • Only 4.9% included a measure of interpersonal discrimination.
   • The terms white racism and white supremacy did not appear in any of the 324 articles.
   • 62.3% examined traits, behaviors, biomarkers, neighborhoods, or other characteristics of disadvantaged groups.
4. National Policy (Healthy People 2000 to 2030 series):
   • Across all four decades of Healthy People initiatives, recommendations primarily focused on changing the behaviors and circumstances of disadvantaged populations, including smoking, diet, exercise, and use of preventive health services. 
   • The authors also highlight a Centers for Disease Control and Prevention (CDC) equity infographic depicting the solution to inequity as “boosting” the shorter (disadvantaged) person without questioning the position or behavior of the taller (advantaged) person.

Important note on causality: The authors emphasize that health-inequality diversions are documented as a recurring pattern across multiple stages of the research process rather than a proven causal mechanism. They present several potential explanations for these diversions, including researcher discomfort, indifference, self-interest in protecting privilege, and institutional constraints embedded within the existing research canon. They also call for further research into why these diversions occur. 

Conclusions

The authors offer the following recommendations for the field:

• Sociologists should lead. Medical sociologists are especially well-positioned to integrate insights from race, class, and inequality theory into health research, including frameworks like Feagin’s systemic racism, Bonilla-Silva’s colorblind racism, Tilly’s concept of opportunity hoarding, and Tomaskovic-Devey and Avent-Holt’s relational inequality theory.
• Expand measurement. Survey research must develop new measures that capture the source and context of discriminatory acts– including who perpetrated them, where they occurred, and under what conditions–  rather than focusing solely on measuring downstream health effects experienced by those subjected to discrimination. 
• Directly study advantaged groups. Researchers should use qualitative fieldwork, audit studies, and experimental methods to examine how privileged groups actively maintain health advantages and exclude others.
• Address the socioeconomic discrimination gap. While measures of racial discrimination are underdeveloped in health research, measures of class-based discrimination are nearly nonexistent. Both must be developed and incorporated into future research. 

Policy implication: The authors argue that because policy is shaped by the research canon, health-inequality diversions are reflected in diversionary policies and programs that target the behaviors of disadvantaged populations rather than challenging the conditions advantaged groups create and maintain. They contend that a reorientation of research toward the actions of the advantaged would, over time, produce more accurate and effective policy responses to health inequalities.

This article makes an important conceptual contribution to antiracist research practice by naming and documenting health-inequality diversions. In doing so, it provides a framework for structural bias in the health sciences, one that protects advantaged groups from accountability while placing the burden of explanation and intervention on those already harmed by inequality.