ArticleAmerican journal of epidemiology2020
Invited Commentary: Making Causal Inference More Social and (Social) Epidemiology More Causal.
Article in American journal of epidemiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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Who cites it
23 citing papers in PubMed.
- Mediation effects that emulate a target randomised trial: Simulation-based evaluation of ill-defined interventions on multiple mediators.Statistical methods in medical research · 2021Trial
- How power is conceptualized and operationalized in evidence-based intervention implementation: a scoping review.Implementation science : IS · 2026Article
- Causal Inference in Health Disparities Research.Annual review of public health · 2026Review
- Challenges in estimating effects of hypothetical interventions on resources patterned by structural racism: an example in a rural North Carolina Medicaid population.American journal of epidemiology · 2026Article
- Covariate adjustment in LGBTQ+ health disparities research: aligning methods with assumptions.American journal of epidemiology · 2026Article
- Complex methods for complex data: key considerations for interpretable and actionable results in exposome research.European journal of epidemiology · 2025Article
- The Target Study: A Conceptual Model and Framework for Measuring Disparity.Sociological methods & research · 2025Article
- Poverty and Childhood Obesity: Current Evidence and Methodologies for Future Research.Current obesity reports · 2025Review
- Reconceptualizing rurality: Exploring community capital to identify distinct rural classes in the United States.SSM - population health · 2025Article
- A Review of the Causal Decomposition Framework for Modeling Interventions that Reduce Disparities.Current epidemiology reports · 2025Article
- The causal impact of segregation on a disparity: A gap-closing approach.Sociological science · 2025Article
- The gap-closing estimand: A causal approach to study interventions that close disparities across social categories.Sociological methods & research · 2024Article
- Selection Bias in Health Research: Quantifying, Eliminating, or Exacerbating Health Disparities?Current epidemiology reports · 2024Article
- Evaluating Clinic-Based Interventions to Reduce Racial Differences in Mortality Among People With Human Immunodeficiency Virus in the United States.The Journal of infectious diseases · 2023Article
- Co-occurring psychiatric disorders and disparities in buprenorphine utilization in opioid use disorder: An analysis of insurance claims.Drug and alcohol dependence reports · 2023Article
- Childhood socioeconomic position and cardiometabolic risk in young adulthood- the impact of mental health.BMC public health · 2023Article
- Invited Commentary: Conducting and Emulating Trials to Study Effects of Social Interventions.American journal of epidemiology · 2022Article
- Structural Racism and Quantitative Causal Inference: A Life Course Mediation Framework for Decomposing Racial Health Disparities.Journal of health and social behavior · 2022Article
- Complex systems models for causal inference in social epidemiology.Journal of epidemiology and community health · 2021Article
- Meaningful Causal Decompositions in Health Equity Research: Definition, Identification, and Estimation Through a Weighting Framework.Epidemiology (Cambridge, Mass.) · 2021Article
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Abstract
A society's social structure and the interactions of its members determine when key drivers of health occur, for how long they last, and how they operate. Yet, it has been unclear whether causal inference methods can help us find meaningful interventions on these fundamental social drivers of health. Galea and Hernán propose we place hypothetical interventions on a spectrum and estimate their effects by emulating trials, either through individual-level data analysis or systems science modeling (Am J Epidemiol. 2020;189(3):167-170). In this commentary, by way of example in health disparities research, we probe this "closer engagement of social epidemiology with formal causal inference approaches." The formidable, but not insurmountable, tensions call for causal reasoning and effect estimation in social epidemiology that should always be enveloped by a thorough understanding of how systems and the social exposome shape risk factor and health distributions. We argue that one way toward progress is a true partnership of social epidemiology and causal inference with bilateral feedback aimed at integrating social epidemiologic theory, causal identification and modeling methods, systems thinking, and improved study design and data. To produce consequential work, we must make social epidemiology more causal and causal inference more social.
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