Faculty Bibliography

Directed acyclic graphs (DAGs), a prominent tool for expressing assumptions in epidemiologic research, are most useful when the hypothetical data generating structure is correctly encoded. Understanding a study's data generating structure and translating that data structure into a DAG can be challenging, but these skills are often glossed over in training. Campbell and Stanley's framework for causal inference has been extraordinarily influential in social science training programs but has received less attention in epidemiology. Their work, along with subsequent revisions and enhancements based on practical experience conducting empirical studies, presents a catalog of 37 threats to validity describing reasons empirical studies may fail to deliver causal effects. We interpret most of these threats to study validity as suggestions for common causal structures. Threats are organized into issues of statistical conclusion validity, internal validity, construct validity, or external validity. To assist epidemiologists in drawing the correct DAG for their application, we map the correspondence between threats to validity and epidemiologic concepts that can be represented with DAGs. Representing these threats as DAGs makes them amenable to formal analysis with d-separation rules and breaks down cross-disciplinary language barriers in communicating methodologic issues.

Population health researchers from different fields often address similar substantive questions but rely on different study designs, reflecting their home disciplines. This is especially true in studies involving causal inference, for which semantic and substantive differences inhibit interdisciplinary dialogue and collaboration. In this paper, we group nonrandomized study designs into two categories: those that use confounder-control (such as regression adjustment or propensity score matching) and those that rely on an instrument (such as instrumental variables, regression discontinuity, or differences-in-differences approaches). Using the Shadish, Cook, and Campbell framework for evaluating threats to validity, we contrast the assumptions, strengths, and limitations of these two approaches and illustrate differences with examples from the literature on education and health. Across disciplines, all methods to test a hypothesized causal relationship involve unverifiable assumptions, and rarely is there clear justification for exclusive reliance on one method. Each method entails trade-offs between statistical power, internal validity, measurement quality, and generalizability. The choice between confounder-control and instrument-based methods should be guided by these tradeoffs and consideration of the most important limitations of previous work in the area. Our goals are to foster common understanding of the methods available for causal inference in population health research and the tradeoffs between them; to encourage researchers to objectively evaluate what can be learned from methods outside one's home discipline; and to facilitate the selection of methods that best answer the investigator's scientific questions.

The Robert Wood Johnson Foundation (RWJF)'s Culture of Health Action Framework guides a movement to improve health and advance health equity across the nation. Action Area One of the Framework, Making Health a Shared Value, highlights the role of individual and community factors in achieving a societal commitment to health and health equity, centered around three drivers: Mindset and Expectations, Sense of Community, and Civic Engagement. To stimulate research about how Action Area One and its drivers may impact health, Evidence for Action (E4A), a signature research funding program of RWJF, developed and released a national Call for Proposals (CFP). The process of formulating the CFP and reviewing proposals surfaced important challenges for research on creating and sustaining shared values to foster and maintain a Culture of Health. In this essay, we describe these considerations and provide examples from funded projects regarding how challenges can be addressed.

BACKGROUND:Community violence is an understudied aspect of social context that may affect risk of preterm birth and small-for-gestational age (SGA). METHODS:We matched California mothers with live singleton births who were exposed to a homicide in their Census tract of residence in 2007-2011 to unexposed mothers within the same tract. We estimated risk differences with a weighted linear probability model, with weights corresponding to the matched data structure. We estimated the average treatment effect on the treated of homicide exposure on the risk of preterm birth and SGA during the preconception period and first and second trimester. RESULTS:We found a small increase in risk of SGA associated with homicide exposure in the first trimester (0.14% [95% confidence interval (CI) = -0.01%, 0.30%]), but not for exposure during the preconception period (-0.01% [95% CI = -0.17%, 0.15%]) or the second trimester (-0.06% [95% CI = -0.23%, 0.11%]). Risk of preterm birth was not affected by homicide exposure. When women were exposed to homicides during all three exposure windows, there was a larger increase in risk of SGA (1.09% [95% CI = 0.15%, 2.03%]) but not preterm birth (0.14% [95% CI = -0.74%, 1.01%]). Exposure to three or more homicides was also associated with greater risk of SGA (0.78% [95% CI = 0.15%, 1.40%]). Negative controls indicated that residual confounding by temporal patterning was unlikely. CONCLUSIONS:Homicide exposure during early pregnancy is associated with a small increased risk of SGA.

Police use of force is an important public health issue in the US. Recent high-profile incidents suggest a potential link between mental disorders and police use of force, however little research has examined their co-occurrence in the general population. We aimed to assess the overall association between specific mental and substance use disorders (MSUDs) and nonfatal legal intervention injury. We identified nonfatal legal intervention injury cases (n = 90,099) and MSUD diagnoses from all hospital and emergency department (ED) records in California between 2005 and 2014. Age-, sex-, and race-standardized MSUD prevalence estimates among legal intervention injury cases, stratified by inpatient status, were compared to general US population-based estimates from the National Comorbidity Survey Replication. Compared to the general US population, nonaffective psychoses, mood disorders, alcohol use disorders, and drug use disorders were substantially overrepresented among inpatient legal intervention injuries (prevalence difference [PD]: 19.2%, (95% confidence interval [CI]: 18.0, 20.4); PD: 15.3%, (95% CI: 13.9, 16.7); PD: 21.1%, (95% CI: 19.8, 22.4); PD: 29.7%, (95% CI: 28.4, 31.0), respectively). Associations for all except mood disorders were similar but attenuated among ED injury cases. In contrast, anxiety disorders were underrepresented in both inpatient and ED injury cases. Results for mood disorders and suicidal ideation were mixed. In summary, MSUDs characterized by more overt behavioral symptoms were substantially overrepresented among legal intervention injury cases. Findings support the potential importance of interventions to improve treatment and law enforcement recognition of such disorders. Additional research should disentangle the complex relationship between MSUDs and legal intervention injury.