Violence changes the life course of far too many young people in the United States. Homicide, the most extreme consequence of interpersonal violence, led to 2043 deaths among adolescents ages 13 to 20 years in 2013,¹ with the highest incidence concentrated in urban settings and among African American youths.² Medical advances have reduced assault case-fatality rates, but declines over the last 25 years have stagnated as we reach the limits of what postinjury medical care can do to save critically injured youths.²

In the United States, race-based disparities in cardiovascular disease care have proven to be pervasive, deadly, and expensive. African American/Black, Hispanic/Latinx, and Native/Indigenous American individuals are at an increased risk of cardiovascular disease and are less likely to receive high-quality, evidence-based medical care as compared with their White American counterparts. Although the United States population is diverse, the cardiovascular workforce that provides its much-needed care lacks diversity. The available data show that care provided by physicians from racially diverse backgrounds is associated with better quality, both for minoritized patients and for majority patients. Not only is cardiovascular workforce diversity associated with improvements in health care quality, but racial diversity among academic teams and research scientists is linked with research quality. We outline documented barriers to achieving workforce diversity and suggest evidence-based strategies to overcome these barriers. Key strategies to enhance racial diversity in cardiology include improving recruitment and retention of racially diverse members of the cardiology workforce and focusing on cardiovascular health equity for patients. This review draws attention to academic institutions, but the implications should be considered relevant for nonacademic and community settings as well.

Objective/Aim: We describe best practices for modeling egocentric networks and health outcomes using a five-step guide. Background: Social network analysis (SNA) is common in social science fields and has more recently been used to study health-related topics including obesity, violence, substance use, health organizational behavior, and healthcare utilization. SNA, alone or in conjunction with spatial analysis, can be used to uniquely evaluate the impact of the physical or built environment on health. The environment can shape the presence, quality, and function of social relationships with spatial and network processes interacting to affect health outcomes. While there are some common measures frequently used in modeling the impact of social networks on health outcomes, there is no standard approach to social network modeling in health research, which impacts rigor and reproducibility. Methods: We provide an overview of social network concepts and terminology focused on egocentric network data. Egocentric, or personal networks, take the perspective of an individual who identifies their own connections (alters) and also the relationships between alters. Results: We describe best practices for modeling egocentric networks and health outcomes according to the following five-step guide: (1) model selection, (2) social network exposure variable and selection considerations, (3) covariate selection related to sociodemographic and health characteristics, (4) covariate selection related to social network characteristics, and (5) analytic considerations. We also present an example of SNA. Conclusions: SNA provides a powerful repertoire of techniques to examine how relationships impact attitudes, experiences, and behaviors—and subsequently health.

Violence is pervasive and leads to significant morbidity and mortality.¹ Male youth in urban neighborhoods bear a disproportionate burden of individual and community violence exposure, which has been linked to increased risk of violence perpetration.^2-10 Historically, violence research has tended to focus narrowly on single types of violence (eg, youth violence perpetration) and associated risk and protective factors. In 2014, the Centers for Disease Control and Prevention released a pivotal report, Connecting the Dots: An Overview of the Links Among Multiple Forms of Violence,¹¹ which outlined interconnections among different types of violence perpetration and exposure and highlighted the urgent need for cross-cutting epidemiological and prevention studies. Understanding nuanced patterns across types of violence perpetration and associated exposures, and how these patterns align with multiple risk and protective factors among male youth in urban neighborhoods, can identify targets for intervention.