Network Mixing and Network Influences Most Linked to HIV Infection and Risk Behavior in the HIV Epidemic Among Black Men Who Have Sex With Men

Objectives. We evaluated network mixing and influences by network members upon Black men who have sex with men.Methods. We conducted separate social and sexual network mixing analyses to determine the degree of mixing on risk behaviors (e.g., unprotected anal intercourse [UAI]). We used logistic regression to assess the association between a network “enabler” (would not disapprove of the respondent’s behavior) and respondent behavior.Results. Across the sample (n = 1187) network mixing on risk behaviors was more assortative (like with like) in the sexual network (r_sex, 0.37–0.54) than in the social network (r_social, 0.21–0.24). Minimal assortativity (heterogeneous mixing) among HIV-infected men on UAI was evident. Black men who have sex with men reporting a social network enabler were more likely to practice UAI (adjusted odds ratio = 4.06; 95% confidence interval = 1.64, 10.05) a finding not observed in the sexual network (adjusted odds ratio = 1.31; 95% confidence interval = 0.44, 3.91).Conclusions. Different mixing on risk behavior was evident with more disassortativity among social than sexual networks. Enabling effects of social network members may affect risky behavior. Attention to of high-risk populations’ social networks is needed for effective and sustained HIV prevention.The HIV epidemic among men who have sex with men (MSM) has not only grown to alarming levels overall, but it also is one that demonstrates significant and marked racial disparities. In 2008, 28% of MSM with new HIV infection were Black, and among MSM aged 13 to 29 years, the number of new infections in Black MSM was nearly twice that of White MSM.1,2Traditional epidemiological approaches have made limited headway in explaining these findings because they tend to focus on the role of individual risk behaviors in shaping rates of HIV infection. The higher rates of HIV among Black MSM may not be explained by individual-level risk behaviors alone, and instead may be attributed in part to social and sexual network factors.3,4 But efforts to further illuminate these factors have been largely unsuccessful as they have often used sampling methodologies that can distort accurate measurement of existing networks of these MSM (e.g., lack of weighting and focus on most recent sexual partner).5,6 Furthermore, up until now, network analyses have not examined Black MSM’s nonsexual social networks; such networks may contribute to the disparities observed (e.g., lack of embedded social network members7) and might provide opportunities for future interventions.Some research has explained disparities in HIV rates by examining sexual network mixing patterns within and between racial subgroups.8,9 Previously, we demonstrated that higher rates of sexually transmitted infections (STIs) within the African American community were related to sexual network mixing patterns.10 Higher levels of disassortative mixing—core high-risk groups mixing with peripheral low-risk groups—within the African American community, combined with limited interracial mixing, was a major contributor for the disproportionately higher rates of STIs among Blacks than among Whites. Similar sexual network mixing explanations have been demonstrated among Blacks in the Southeastern United States.11 Drug use behavior was found to be highly assortative (like behavior with like), whereas sexual behavior in the form of concurrent (or simultaneous) partnerships was minimally assortative.In contrast to the attention devoted to sexual12–17 and drug-use networks,18–23 comparatively little research has been conducted on how nonrisk social networks comprising MSM’s close friends and family members can affect STI and HIV transmission, with a few notable exceptions.7,24,25 Social learning and differential association theories26,27 hold that risky behaviors, including rationalizations for them, diffuse through social networks of close ties. Furthermore, network members influence high-risk behavior by virtue of the behavioral examples they provide, the normative pressures they exert, and MSM’s perceptions of these influences.28–30 Research has shown in a variety of contexts that risky sexual and substance use behavior is affected by individuals’ perceptions of what their network members do, regardless of whether those perceptions are accurate.31–33 Studying Black MSM’s normative contexts may help researchers identify not only those social conditions that facilitate risky behavior, but also potential network influences that can be exploited or modified to encourage the spread of HIV prevention behavior through modification of a social network. To date, most work that has examined the indirect role of social networks on the spread of HIV has focused primarily on the role of having social network ties in general, but has not specified the mechanisms through which social network ties affect the risk behavior of MSM.34,35Formal social network analysis of high-risk populations has focused on MSM and injecting drug users in general and not specifically on Black MSM.25,36 One recent pilot study37 demonstrated that sexual partners of Black MSM were mostly introduced through friends. Known risk behaviors associated with HIV infection and that could be “transmitted” through a social network include sex-drug use38 and unprotected anal intercourse (UAI). Moreover, group sexual intercourse has also recently gained increased attention as an important risk practice39,40 that can complicate network analysis.41 Important influences and practices such as these, however, have not been previously explored through social network analysis within Black MSM despite this population’s position as a group with the highest risk of HIV infection in the United States. Furthermore, network patterns that potentially confer risk, such as disassortative social mixing, have also not been explored within this population as opposed to the larger Black community.10,11 We conducted a detailed analysis of close social and sexual networks of Black MSM to determine the salient properties and components of these networks that are most related to HIV risk and preventive behavior among these men.     

The Relationship Between Gun Ownership and Stranger and Nonstranger Firearm Homicide Rates in the United States, 1981–2010

Objectives. We examined the relationship between gun ownership and stranger versus nonstranger homicide rates.Methods. Using data from the Supplemental Homicide Reports of the Federal Bureau of Investigation’s Uniform Crime Reports for all 50 states for 1981 to 2010, we modeled stranger and nonstranger homicide rates as a function of state-level gun ownership, measured by a proxy, controlling for potential confounders. We used a negative binomial regression model with fixed effects for year, accounting for clustering of observations among states by using generalized estimating equations.Results. We found no robust, statistically significant correlation between gun ownership and stranger firearm homicide rates. However, we found a positive and significant association between gun ownership and nonstranger firearm homicide rates. The incidence rate ratio for nonstranger firearm homicide rate associated with gun ownership was 1.014 (95% confidence interval = 1.009, 1.019).Conclusions. Our findings challenge the argument that gun ownership deters violent crime, in particular, homicides.Firearms cause more than 31 000 deaths annually in the United States.1 Since the tragic shooting of 20 children and 7 adults in Newtown, Connecticut, in 2012, several states have enacted or debated legislation to restrict the availability of firearms.2 Some gun rights advocates have argued that restricting the availability of guns might cause harm by removing an effective deterrent to crime.3-5 Lott, for example, has suggested that reducing the number of guns held by law-abiding citizens might increase homicides because “it would be easier for criminals to prey on the weakest citizens, who would find it more difficult to defend themselves.”5^(p11) Understanding whether increased gun ownership increases or decreases homicides is essential to inform public policy regarding measures to address firearm violence.Of particular interest is the question of whether higher gun ownership is associated with lower rates of stranger homicide (i.e., homicide committed by a person unknown to the victim) because such a relationship is consistent with the hypothesis that increased household ownership of guns deters violent crime by strangers who might otherwise have killed the potential victim.Multiple cross-sectional studies have demonstrated a correlation between higher gun ownership at the state level and higher overall state-specific rates of firearm homicide.6-18 Most recently, we reported a strong and robust relationship between estimated gun ownership in the 50 states and firearm homicide rates over the period 1981 to 2010, while controlling for 20 potential state-level confounding variables.19 None of these studies distinguished between stranger and nonstranger homicides. We are not aware of any published studies that have examined the relationship between gun ownership and stranger versus nonstranger homicide rates.Although the US Department of Justice regularly provides national statistics on rates of stranger versus nonstranger homicide,20,21 we are aware of no published studies that report state-specific data on stranger versus nonstranger homicide. Understanding state-specific patterns of victimization in terms of the relationship between homicide victims and offenders, and identifying the trends in these patterns, would inform state efforts to reduce homicide rates.22Several studies have examined the relationship between homicide victims and offenders in specific settings, such as national youth homicides22; national homicides23,24; Allegheny County, Pennsylvania, homicides25; adolescent homicides in North Carolina26; homicides in Contra Costa County, California27; and national homicides among intimate partners.28 Nationally, between 1980 and 2008, of the homicides for which the relationship between victim and offender was known (63.1% of all homicides), approximately one fifth (21.9%) were stranger homicides.20 We are not aware of any published data on how this may vary among states.In this article, we report and analyze stranger and nonstranger homicides at the state level during the period 1981 to 2010 and examine the relationship between those rates and state-specific household gun ownership during the same years. To the best of our knowledge, ours is the first study to report state-specific data on stranger and nonstranger homicide rates and examine the relationship between state-level gun ownership and stranger and nonstranger homicide rates, while controlling for differences in a wide range of state-level factors associated with homicide.     

The Relationship Between Gun Ownership and Firearm Homicide Rates in the United States, 1981–2010

Objectives. We examined the relationship between levels of household firearm ownership, as measured directly and by a proxy—the percentage of suicides committed with a firearm—and age-adjusted firearm homicide rates at the state level.Methods. We conducted a negative binomial regression analysis of panel data from the Centers for Disease Control and Prevention’s Web-Based Injury Statistics Query and Reporting Systems database on gun ownership and firearm homicide rates across all 50 states during 1981 to 2010. We determined fixed effects for year, accounted for clustering within states with generalized estimating equations, and controlled for potential state-level confounders.Results. Gun ownership was a significant predictor of firearm homicide rates (incidence rate ratio = 1.009; 95% confidence interval = 1.004, 1.014). This model indicated that for each percentage point increase in gun ownership, the firearm homicide rate increased by 0.9%.Conclusions. We observed a robust correlation between higher levels of gun ownership and higher firearm homicide rates. Although we could not determine causation, we found that states with higher rates of gun ownership had disproportionately large numbers of deaths from firearm-related homicides.The December 14, 2012, tragic shooting of 20 children and 7 adults in Newtown, Connecticut, brought the issue of controlling firearm-related mortality to the forefront.1–5 The National Rifle Association responded by calling for armed guards and teachers in all schools.6 Hundreds of teachers have flocked to gun-training classes, motivated by the contention that increasing the presence of guns can reduce firearm-related deaths.7 Firearms are responsible for more than 31 000 deaths and an estimated 74 000 nonfatal injuries among US residents each year,8 most of which are violence related. Understanding the relationship between the prevalence of gun ownership (and therefore the availability of guns) and firearm-related mortality is critical to guiding decisions regarding recently proposed measures to address firearm violence.Several lines of research have explored the relationship between firearm prevalence and homicide rates.9 Studies have shown that individual gun ownership is related to an increased risk of being a homicide victim.10–12 These studies are limited because they only examine the individual risks or benefits of gun ownership. They cannot be used to assess whether the prevalence of gun ownership in the population affects overall homicide rates.9 Ecological studies have correlated higher levels of gun ownership rates in the United States with higher national rates of homicide than are experienced in other countries.13–19 Although these studies suggest a relationship between gun ownership and homicide, they are severely limited because of inadequate adjustment for confounding factors.9Examination of variation in homicide rates between cities, regions, or states within the United States in relation to differences in gun ownership provides a stronger line of research. A few studies have used a time-series design to investigate the relationship between firearm ownership and homicide over a period of years, either analyzing changes over time within cities or states20–23 or examining changes over time across states.24–29 Several studies used cross-sectional analyses to detect a positive relationship between the prevalence of gun ownership at the neighborhood,30 county,31,32 regional,31,33–36 or state level32,34–45 and homicide rates, with control for differences in factors associated with homicide (e.g., urbanization, race/ethnicity, unemployment, poverty, crime, and alcohol use). Most data used in these studies represented only a cross-section in time; only 4 contained panel data over multiple years. Sorenson and Berk used data from 1972 to 1993,23 Bordura examined data for 1973 to 1981,31 Miller et al. published 3 analyses of panel data from 1988 to 1997,34–36 and Cook and Ludwig used panel data for 1980 to 1999.32 None of the existing panel studies examined data more recent than 1999.32Studies analyzing data over long periods are valuable because they assess the effects of variation in gun availability not only between states but within states over time. Although we are aware of no multiyear studies of interstate variation in gun ownership and homicide rates since 1999, national data from the General Social Survey show that the prevalence of household gun ownership has decreased by approximately 12% since then.46 This presents an opportunity not only to bring the existing literature up to date, but also to investigate temporal changes in gun ownership to explore its potential relationship with changes in homicide rates, within and between states. Annual, state-specific homicide data are readily available from as early as 1981 and as recently as 2010.8 During this period, the prevalence of gun ownership decreased by about 36%.46 Thus, it is feasible and useful to study the relationship between gun availability and homicide across states over the entire period 1981 to 2010.We expanded on previous work by incorporating the most recent data, analyzing data over 3 decades, and controlling for an extensive panel of annual, state-specific factors that might confound the association between gun ownership and firearm homicide rates. We examined the relationship between gun ownership and age-adjusted firearm homicide rates across all 50 states during the 30-year period 1981 through 2010, with adjustment for age, gender, race/ethnicity, urbanization, poverty, unemployment, income, education, income inequality, divorce rate, alcohol use, violent crime rate, nonviolent crime rate, hate crime rate, number of hunting licenses, age-adjusted nonfirearm homicide rate, incarceration rate, and suicide rate. To the best of our knowledge, this was the most comprehensive study to date, both in number of years in the analysis and breadth of control variables.     

Mitigating HIV Health Disparities: The Promise of Mobile Health for a Patient-Initiated Solution

The HIV epidemic is an ongoing public health problem fueled, in part, by undertesting for HIV. When HIV-infected people learn their status, many of them decrease risky behaviors and begin therapy to decrease viral load, both of which prevent ongoing spread of HIV in the community.Some physicians face barriers to testing their patients for HIV and would rather their patients ask them for the HIV test. A campaign prompting patients to ask their physicians about HIV testing could increase testing.A mobile health (mHealth) campaign would be a low-cost, accessible solution to activate patients to take greater control of their health, especially populations at risk for HIV. This campaign could achieve Healthy People 2020 objectives: improve patient–physician communication, improve HIV testing, and increase use of mHealth.World AIDS Day each December reminds us of the ongoing HIV epidemic in the United States and its disproportionate toll on racial and ethnic minority communities. HIV testing is an essential strategy to curb the ongoing epidemic. When people infected with HIV learn their status, many of them decrease risky behaviors to prevent spread to others1 and begin antiretroviral therapy to decrease viral load, the main biological predictor of the ongoing spread of HIV in the community.2 Despite national recommendations to make HIV testing routine for all adults,3–6 HIV testing rates—particularly among the racial and ethnic communities hardest hit—remain low.7 Patients want to be tested.8 However, physicians face numerous HIV testing barriers, including physician discomfort with initiating HIV testing discussions,9 physicians not realizing that patients expect HIV testing to be done,8 time,10,11 and competing clinical priorities.11,12A pioneering intervention to improve HIV testing in health care settings may be a patient-initiated approach. The push–pull capacity model offers a framework to guide a solution to improve patient-initiated HIV testing.13,14 With a push–pull model, health information can be provided—or pushed—to many patients. This push creates a demand—or pull—for health services that address patient concerns. The ubiquity of cell phones and the pervasive use of text messaging provide an innovative platform for promoting an effective HIV testing campaign. Operationalizing the push–pull model through mobile health (mHealth) could be a novel approach to improving HIV testing in health care settings. This initiative would reduce demands on physicians, increase patients’ engagement in their own health, and address a significant ongoing public health problem.15 Goals of Healthy People 2020 include eliminating health disparities and increasing the number of people who have been tested for HIV.16     

Intimate Partner Homicide and Corollary Victims in 16 States: National Violent Death Reporting System, 2003–2009

Objectives. We estimated the frequency and examined the characteristics of intimate partner homicide and related deaths in 16 US states participating in the National Violent Death Reporting System (NVDRS), a state-based surveillance system.Methods. We used a combination of quantitative and qualitative methods to analyze NVDRS data from 2003 to 2009. We selected deaths linked to intimate partner violence for analysis.Results. Our sample comprised 4470 persons who died in the course of 3350 intimate partner violence–related homicide incidents. Intimate partners and corollary victims represented 80% and 20% of homicide victims, respectively. Corollary homicide victims included family members, new intimate partners, friends, acquaintances, police officers, and strangers.Conclusions. Our findings, from the first multiple-state study of intimate partner homicide and corollary homicides, demonstrate that the burden of intimate partner violence extends beyond the couple involved. Systems (e.g., criminal justice, medical care, and shelters) whose representatives routinely interact with victims of intimate partner violence can help assess the potential for lethal danger, which may prevent intimate partner and corollary victims from harm.Intimate partner violence (IPV) is a serious public health problem that affects millions in the United States. IPV is defined as physical violence, sexual violence, stalking, or psychological aggression (including coercive tactics) by a current or former intimate partner.1 IPV that is severe enough to lead to injury or significant harm is primarily but not always perpetrated by men. Estimates from the 2010 National Intimate Partner and Sexual Violence Survey indicate that more than 74 million people in the United States have experienced IPV (physical violence, sexual violence, stalking) at some point in their lives, and more than 12 million in the previous 12 months.2 In the United States, IPV disproportionately affects women, especially racial/ethnic minorities.2,3The most extreme form of IPV is intimate partner homicide (IPH). In 2007, intimate partners committed 14% of all US homicides, and 70% of those victims were female.4 Although IPH has decreased during the past 15 to 20 years,4 it remains a disturbing possibility for people experiencing abusive relationships. Across studies, major risk factors for IPH consistently include previous domestic violence, unemployment, access to firearms, estrangement, threats to kill, threats with a weapon, previous nonfatal strangulation, a stepchild in the home (if the victim is female), and previous mental health problems of the perpetrator (for homicide–suicide).5,6 Of these, previous IPV is the strongest predictor.6 Furthermore, homicides followed by suicide of the perpetrator are more than twice as likely to be committed by former or current spouses as by other perpetrators and are significantly more likely to involve firearms than other weapons.6,7 It is estimated that one third of IPHs in the United States involve suicide of the perpetrator, who is most often male.6,8The Centers for Disease Control and Prevention estimates that societal costs resulting from IPV victimization approach $6 billion annually.9 Such cost estimates and scientific studies of IPH have largely focused on intimate partners of the perpetrator (e.g., spousal homicides). However, a substantial portion of IPV-related homicide victims are not the intimate partners themselves. These corollary victims may be family members, friends, neighbors, persons who intervene in IPV, law enforcement responders, or bystanders. Previous studies10,11 have used the term “collateral victims” to refer to non–intimate partner victims in situations stemming from IPV. Because of the colloquial usage of “collateral” and out of concern for the negative connotations associated with the word, we selected the word “corollary” to refer to non–intimate partner victims whose death is connected to IPV.Few studies have examined corollary victims or included them in analyses of IPH.10,11 In one exception, a British study examined murder connected to intimate partner conflict and found that 37% of the 166 victims were not intimate partners of the murderer.10 Instead, the victims were children of the intimate partner, allies (e.g., relatives, neighbors, friends, lawyers connected to the abuse victim), or new partners. In the United States, it is difficult to estimate the magnitude of corollary victimization. Existing data systems, such as the Uniform Crime Reports, often use categories that do not provide the details necessary to understand the relationships among the victims and offenders.12 For example, if an ex-husband kills his ex-wife’s new partner, the new partner may be categorized as an acquaintance. Furthermore, same-sex intimate partners are categorized as acquaintances in lieu of a more specific designation (e.g., romantic partner, domestic partner). At state and local levels, investigations conducted by fatality review boards may reveal the proportion of collateral victims resulting from IPV, but those figures are often not widely reported.We examined IPH data gathered between 2003 and 2009 by the National Violent Death Reporting System (NVDRS), a state-based surveillance system. Our objective was to extend the existing literature on the frequency and characteristics of IPH and on corollary homicides that occur in the context of IPV and IPH.     

Education: A Missed Opportunity for Public Health Intervention

Educational attainment is a well-established social determinant of health. It affects health through many mechanisms such as neural development, biological aging, health literacy and health behaviors, sense of control and empowerment, and life chances. Education—from preschool to beyond college—is also one of the social determinants of health for which there are clear policy pathways for intervention. We reviewed evidence from studies of early childhood, kindergarten through 12th grade, and higher education to identify which components of educational policies and programs are essential for good health outcomes. We have discussed implications for public health interventions and health equity.Social class is a fundamental determinant of health and disease1 and is associated with the persistence of health inequalities.2,3 One of several components that determine social class standing, education contributes to cumulative advantage4 across the life course5 and is strongly associated with both morbidity6–10 and mortality.11–14 Formal education—from preschool to beyond college—is also one of the social determinants of health for which there are clear policy pathways for intervention.12,15,16Uncertainty exists, however, about the specific elements of education that influence health. Is it teacher training, classroom interactions, selective institutions, or something else? To recommend particular types of educational interventions, we must better understand the elements of the education experience that are associated with health and, in particular, whether this association is causal.17,18 The body of educational research on successful educational interventions is still growing. For example, in addition to imparting knowledge, educational institutions may perpetuate societal power structures that help set social norms,19 a phenomenon already identified as important for health.3 Education may also affect health6–10 via neural development,20 biological aging,12,15,16 health literacy and health behaviors,6,17,18,21–23 sense of control and empowerment,24 and life chances (e.g., income and occupation).6,17 Figure 1 illustrates these potential pathways. Each of these mechanisms may have implications that differ for individual health versus population health.Open in a separate windowFIGURE 1—Potential pathways through which education may affect health.Is the amount of education the most important element in the equation? It certainly is the easiest to measure.10 Or is it the quality of education? Or the type of people who seek education? Is it the knowledge imparted? The historical context of the study population matters as well. For example, years of education attained is typically used as a measure of the baseline predictor of neurocognitive status. However, recent studies of older African Americans found that reading level was actually a better predictor of baseline neurocognitive status than were years of schooling25 and that accounting for reading level could perhaps reduce observed racial disparities in cognitive test scores.26 To understand the potential implications of this finding, we must contextualize the study population in the history of education policy. The age of these study participants indicates they attended school pre–Brown v. Board of Education (e.g., in the 1930s and 1940s), and because they were African American, they likely attended segregated schools that were typically of lower quality.27 Reading below grade level is associated with and reflective of having attended a lower quality school.28,29 Additionally, increasing one’s reading level can lead to accumulating other educational advantages; such cumulative advantages can accentuate disparities.4 As a result, one’s reading level may improve neurocognitive health and mitigate health disparities.As illustrated by this example, answering these questions requires a study of 2 bodies of literature that are not often considered together but that share common goals and values.30 We critically reviewed the education literature and the public health literature to summarize what researchers in these fields know and to identify future needed research directions.     

Sex and Gender in the US Health Surveillance System: A Call to Action

Youth Risk Behavior Survey (YRBS) data have exposed significant sexual orientation disparities in health. Interest in examining the health of transgender youths, whose gender identities or expressions are not fully congruent with their assigned sex at birth, highlights limitations of the YRBS and the broader US health surveillance system.In 2009, we conducted the mixed-methods Massachusetts Gender Measures Project to develop and cognitively test measures for adolescent health surveillance surveys. A promising measure of transgender status emerged through this work.Further research is needed to produce accurate measures of assigned sex at birth and several dimensions of gender to further our understanding of determinants of gender disparities in health and enable strategic responses to address them.Healthy People 2020 extends a commitment to

assess health disparities in the US population by tracking rates of illness, death, chronic conditions, behaviors, and other types of outcomes in relation to demographic factors1

and aims to “achieve health equity, eliminate disparities, and improve the health of all groups.”2 Youth Risk Behavior Survey data have exposed significant sexual orientation disparities3–8 in health in jurisdictions that included measures of sexual orientation on their surveys.However, gaps in the US health surveillance system inhibit efforts to improve the health of both transgender people9–11 and the nontransgender (cisgender) majority. Demographic measures that would enable the population to be classified as trans- or cisgender are rarely included in the health surveillance system. Such measures, often used in combination, include sex (assigned at birth), gender identity (current), and transgender status (transgender is an identity for some individuals and an adjective or status for others). Data about additional dimensions of gender (e.g., expression, beliefs about gender) that could be used to tackle persistent health disparities are also not collected, and these gaps represent untapped potential to improve population health.Although sex and gender identity are often static and concordant for the vast majority of Americans, both sex and gender (more broadly) are multidimensional constructs and can vary over time—particularly for transgender people. The term sex refers to biological differences between male, female, and intersex people (hormones, secondary sex characteristics, reproductive anatomy) that can be altered through the use of hormones and surgical interventions.12 The assignment of individuals to a sex category by medical practitioners at birth is typically based on the appearance of external genitalia and is recorded on the birth certificate as male or female (and assumes a legal status). Legal sex can sometimes be changed on legal documents (e.g., birth certificate, driver’s license, passport) through a complex set of legal procedures. Gender has psychological (identity—an internal sense of being a boy or girl, genderqueer, etc.), social (beliefs about gender, the roles that one assumes, community affiliation), and behavioral (gender expression, how one expresses one’s identity through appearance and actions and is perceived by others) dimensions.13Unfortunately, sex and gender are rarely explicitly measured, and when data are collected, a range of measures and approaches are used. In recognition of the importance of sex and gender identity as demographic characteristics of the US population, and variability in their measurement, the Institute of Medicine,14 US Department of Health and Human Services,15 and Centers for Disease Control and Prevention16 have called for a national data standard for sex and research to create valid measures of gender identity. Although the Youth Risk Behavior Survey relies on self-reported sex, other health surveillance surveys, such as the Behavioral Risk Factor Surveillance System,17 are telephone administered and classify respondents as male or female according to the sound of their voice, or, as in the in-person National Health Interview Survey,18 use visual appearance, with direct questioning about the respondent’s sex by the interviewer “if necessary”17 or “not apparent,”18 respectively. These data are used as measures of both sex and gender identity19,20; however, they actually measure the interviewer’s perception of the respondent’s gender identity.Data about other dimensions of gender, such as gender expression and beliefs about gender (the individual-level analog to gender norms, a societal-level construct), are not collected in the health surveillance system, despite growing bodies of research that highlight their importance as health determinants. Research conducted in lesbian, gay, and bisexual, as well as general, primarily heterosexual cisgender samples, indicates that individuals whose gender expression fails to conform to sex-linked social expectations (e.g., masculine girls and women, feminine boys and men) are at increased risk for violence,21–28 discrimination,23 posttraumatic stress disorder,28 and depression.29 Violence23,30–38 and discrimination39–41 against transgender people, who are gender nonconforming by identity or expression in relation to their assigned sex at birth, is commonplace.Research conducted in the general population shows that beliefs about gender (e.g., violence is acceptable, exercising caution is not masculine, being assertive is not feminine)42 are associated with aggression43–47 and alcohol use.44,48 Thus, strategies to ameliorate persistent public health problems, such as high mortality among men from injury, homicide, and suicide,49 might be advanced by the collection of gender data. Long-standing disparities in depression that disfavor women50,51 might also be addressed by reducing girls’ and women’s exposure to violence52 and by modifying emotional coping styles (e.g., rumination is more common among girls and women,53 whereas problem solving is positively associated with masculine traits and negatively associated with depression54).     

Peer Victimization and Sexual Risk Differences Between Lesbian,Gay, Bisexual,Transgender, or Questioning and Nontransgender Heterosexual Youths in Grades 7–12

Objectives. Before and after accounting for peer victimization, we estimated sexual risk disparities between students who self-identified as lesbian, gay, bisexual, transgender, or questioning (LGBTQ) and students who self-identified as nontransgender heterosexual.Methods. Students in grades 7 through 12 in Dane County, Wisconsin, were given the Web-administered Dane County Youth Assessment. One set of analyses was based on a sample that included 11 337 students. Subsequent analyses were based on a sample from which we screened out students who may not have been responding to survey items truthfully. Various multilevel-modeling and propensity-score-matching strategies ensured robustness of the results, examined disparities at lower and higher victimization rates, and explored heterogeneity among LGBTQ-identified youths. Finally, propensity-score-matching strategies estimated LGBTQ–heterosexual disparities in 2 matched samples: a sample that reported higher victimization and one that reported lower victimization.Results. Across 7 sexual risk outcomes, and in middle and high school, LGBTQ-identified youths reported engaging in riskier behavior than did heterosexual-identified youths after we accounted for peer victimization. Risk differentials were present in middle and high school. The LGBTQ group was heterogeneous, with lesbian/gay- and bisexual-identified youths generally appearing most risky, and questioning-identified youths least risky. In the matched sample with lower average victimization rates, LGBTQ-identified youths perceived a greater risk of sexually transmitted infections despite not engaging in sexually risky behavior at significantly higher rates; in the matched sample with higher average victimization rates, all outcomes were significantly different.Conclusions. Demonstrated LGBTQ–heterosexual risk differentials in grades 7 through 8 suggest that interventions need to be implemented during middle school. These interventions should also be differentiated to address the unique risk patterns among LGBTQ subgroups. Finally, models of sexual risk disparities must expand beyond peer victimization.High school–aged youths who self-identify as lesbian, gay, bisexual, transgender, or questioning (LGBTQ) tend to exhibit more risk with regard to sexual behavior (such as the number of sex partners, use of protection, and prevalence of sexually transmitted infections [STIs]) than do their self-identified, nontransgender heterosexual peers.1,2 Across middle and high school, LGBTQ youths are also disproportionately the victims of bullying.3–7 Given LGBTQ youths’ high levels of both sexual risk and victimization, a recent meta-analysis suggested that abuse (including peer victimization, but also parental physical abuse and childhood sexual abuse) may actually contribute to sexual risk disparities between LGBTQ and heterosexual youths.2Victimization may lead to increased sexually risky behavior through several pathways, including heightened feelings of isolation leading to increased desires for sexual fulfillment,8 psychological distress leading to unprotected sex,9 and stigmatization leading to lack of knowledge about sexual-minority identity10 in turn leading to seeking out same-sex activities to navigate identity. In a recent retrospective study of LGBT young adults, those who recalled greater peer victimization during their teenage years were more likely to have ever had an STI and to have been at HIV risk in the past 6 months.11 The focus on victimization has also caught on in the media and in some education reform.12,13 However, researchers have noted that victimization may be only one component in explaining LGBTQ–heterosexual suicide-related risk disparities14,15; thus, it stands to reason that victimization may explain part of LGBTQ–heterosexual sexual risk disparities, but that substantial disparities may remain after victimization is accounted for.We sought to provide a rigorous assessment of sexually risky attitudes and behaviors before and after accounting for peer victimization among a large population-based sample of LGBTQ- and heterosexual-identified youths in middle and high school. In the process, we implemented a novel procedure for screening out potentially mischievous survey responders and a series of propensity-score-matching analyses to estimate LGBTQ–heterosexual sexual risk disparities among matched LGBTQ- and heterosexual-identified students with the same demographic characteristics and levels of peer victimization. The methodological advances implemented here provide a more nuanced view of LGBTQ-identified youths and, thus, may improve the effectiveness of future prevention efforts.     

Cyberbullying Perpetration and Victimization Among Middle-School Students

Objectives. We examined correlations between gender, race, sexual identity, and technology use, and patterns of cyberbullying experiences and behaviors among middle-school students.Methods. We collected a probability sample of 1285 students alongside the 2012 Youth Risk Behavior Survey in Los Angeles Unified School District middle schools. We used logistic regressions to assess the correlates of being a cyberbully perpetrator, victim, and perpetrator–victim (i.e., bidirectional cyberbullying behavior).Results. In this sample, 6.6% reported being a cyberbully victim, 5.0% reported being a perpetrator, and 4.3% reported being a perpetrator–victim. Cyberbullying behavior frequently occurred on Facebook or via text messaging. Cyberbully perpetrators, victims, and perpetrators–victims all were more likely to report using the Internet for at least 3 hours per day. Sexual-minority students and students who texted at least 50 times per day were more likely to report cyberbullying victimization. Girls were more likely to report being perpetrators–victims.Conclusions. Cyberbullying interventions should account for gender and sexual identity, as well as the possible benefits of educational interventions for intensive Internet users and frequent texters.Cyberbullying is the “willful and repeated harm inflicted [on another] through the use of computers, cell phones, or other electronic devices.”1^(p5) Among 6th- through 10th-grade students nationally, 4% reported being cyberbullying perpetrators, 5% reported being a victim of cyberbullying, and 5% reported being perpetrators–victims (meaning that they have both perpetrated and been victimized by cyberbullying) during the previous 2 months.2 Among middle-school students in the southeastern and northwestern United States, a nonprobability sample of 3767 students by Kowalski and Limber3 found that 11% reported being a victim of cyberbullying, 4% were cyberbullying perpetrators, and 7% were perpetrators–victims during the previous 2 months. Cyberbullying may be more insidious than traditional bullying, because cyberbullying can quickly reach wide audiences (e.g., e-mails sent to an entire school), can be perpetrated anonymously, and is not bound to in-person interactions.4,5 Although cyberbullying has garnered widespread media attention, to our knowledge, no previous study has explored correlates of cyberbullying with a representative probability sample in an urban middle-school sample.Cyberbullying is associated with a host of health and behavioral health consequences. Research has suggested that cyberbullying may have a greater effect on depression and suicidal ideation than traditional offline bullying.6 Both perpetration and victimization are associated with mental health consequences, including lower self-esteem,7 recent depressive symptoms,5,8,9 and suicidal ideation.5,8,10 Cyberbullying perpetrators are more likely to have problems with their behavior, peer relationships, and emotions, and are less likely to be prosocial than their peers who are neither cyberbullying perpetrators nor victims of cyberbullying.11 Specifically, female cyberbullying perpetrators express greater anxiety and depression than their female peers who are not cyberbullying perpetrators.12 Cyberbullying victimization is also strongly associated with substance use, violent behavior, and risky sexual behavior among high-school students.10Cyberbullying disproportionately affects youths who are already vulnerable to mental health and behavioral health disparities, including members of sexual minorities (i.e., gay, lesbian, bisexual), girls, and racial and ethnic minorities. More than half of sexual-minority middle- and high-school students nationally report being a cyberbully victim during the previous year, with almost one fifth reporting often or frequent victimization.13 Female students are significantly more likely to be cyberbully perpetrators–victims than their male peers.9,14 Studies have reported that male students are significantly more likely to be cyberbullying perpetrators2,15 and significantly less likely to be cyberbully victims.2,6,9 Middle-school boys are more likely to cyberbully others because of their race, sexual identity, or both.16 African American students are more likely to be cyberbully perpetrators and Hispanic students are more likely to be cyberbully perpetrators–victims than their White peers.2Cyberbullying may occur across a variety of technology platforms, and the specific qualities of each platform may affect how cyberbullying is perpetrated and experienced. Earlier studies suggested that instant messaging, chat rooms, and message boards were the most common mediums for middle-school students who experienced cyberbullying.3,17 More recently, youths have migrated to social media platforms such as Facebook,18–20 necessitating an examination of cyberbullying across more contemporary and emerging platforms for youth interaction.More frequent use of technology has also been associated with cyberbullying. Students who use the Internet for at least 3 hours per day and those who use instant messaging and Web cams are significantly more likely to have been cyberbully victims at least 7 times during the previous year.17 Frequent Internet users are significantly more likely to be cyberbully perpetrators, victims, and perpetrators–victims.14Research has shown that even though cyberbullying takes place in a virtual space, most cyberbullying perpetrators know their victims and vice versa. Moreover, 73% of victims reported being “pretty sure” or “totally sure” about the identity of their cyberbully, with 51% of cyberbullying perpetrators identified as a classmate, 43% as someone who they only knew online, and 20% as an in-person, nonclassmate relation.17 Cyberbullying perpetrators of middle-school victims were most often a classmate or a stranger; cyberbullying perpetrators most often reported that they cyberbullied classmates, friends, and strangers.3This study expanded previous work with high-school samples2 and nonprobability samples of middle-school students3,17 to explore the role of sexual identity, gender, race, and technology use patterns in a random sample of urban middle-school students in Los Angeles County, California. The study focused on demographic characteristics including sexual identity, patterns of technology use (i.e., frequency of Internet use, texting, parental rules regarding Internet use), and platforms on which middle-school students experience cyberbullying (i.e., Facebook, Twitter, e-mail, text messaging) to inform interventions to disrupt this maladaptive behavior and help protect early adolescents from the consequences of cyberbullying.     

Tobacco Industry Use of Personal Responsibility Rhetoric in Public Relations and Litigation: Disguising Freedom to Blame as Freedom of Choice

We examined the tobacco industry’s rhetoric to frame personal responsibility arguments. The industry rarely uses the phrase “personal responsibility” explicitly, but rather “freedom of choice.” When freedom of choice is used in the context of litigation, the industry means that those who choose to smoke are solely to blame for their injuries. When used in the industry’s public relations messages, it grounds its meaning in the concept of liberty and the right to smoke. The courtroom “blame rhetoric” has influenced the industry’s larger public relations message to shift responsibility away from the tobacco companies and onto their customers. Understanding the rhetoric and framing that the industry employs is essential to combating this tactic, and we apply this comprehension to other industries that act as disease vectors.Throughout the history of tobacco control, as concerns over health have prompted public calls for reform, the tobacco industry has attempted to combat criticism and influence public health debates through the use of rhetorical techniques that deflect attention from corporate responsibility.1,2 The tobacco industry’s use of personal responsibility frames, or arguments, to protect its business interests against litigation3^{(p870–873),}4^(p820),5–8 and regulation and tobacco control measures9,10^{(p197–198),}11–14^(p406) has been widely recognized. Although previous studies have enumerated and described many of the key frames employed by the tobacco industry and its allies, there is still important work to be done in more rigorously analyzing the relationships between the content of this rhetoric and its origin in either the legal or public relations (PR) context. Such an analysis helps illuminate the importance of subtle variations in the deployment of similar language to convey diverse meanings that can sway public opinion and regulators’ actions.15 This study also can inform efforts aimed at other industries that produce products that have a negative impact on public health, such as sugar-sweetened beverages (SSBs) and junk food, all of which employ techniques the tobacco industry originated and perfected.16Framing refers to the use of key concepts familiar to the listener that help guide the understanding of an issue.17 In particular, frames structure for the audience the cause of social problems and prescribe which actors should and should not act to address them.18 Powerful default frames such as personal responsibility indicate that those who suffer the consequences of consuming certain risky products, such as smokers, are to blame for their injuries and that it is not the role of social institutions such as the government to intervene and protect them.19 Analyzing which frames are present—and absent—in public discourse such as the news is especially valuable as these frames influence policymakers by helping set the agenda for public debates, and signaling which issues are salient and which others are less urgent.20,21The trajectory of the tobacco industry’s use of personal responsibility framing and argumentation began in 1954, when the major US tobacco companies reacted to the release of scientific studies linking smoking and cancer by hiring a PR firm to craft an advertisement called “A Frank Statement to Cigarette Smokers,” which claimed the industry “accept[ed] an interest in people’s health as a basic responsibility, paramount to every other consideration in our business.”9 The industry’s purposely ineffectual efforts to address the dangers of smoking amounted to little more than whitewash and PR rhetoric, with a major emphasis on obfuscation and delay in verifying whether its products were deadly, along with an effort to maintain this as an “open scientific controversy.”In 1964, US Surgeon General Luther Terry released a landmark report that analyzed and evaluated the existing scientific research, concluding that smoking causes disease and death.22 Closely following was the passage of the Federal Cigarette Labeling and Advertising Act (FCLAA) in 1965, which required warning labels on cigarette packages (mandatory warnings for cigarette advertising were later added in 1969) with the tepid and equivocal verbiage “Caution: Cigarette Smoking May Be Hazardous To Your Health.”2,23 At that time the emphasis by the public and regulators was largely on governmental accountability for addressing the problems cigarette smoking caused, while the tobacco industry escaped most culpability and accountability, even weathering the imposition of mandatory warning labels by turning it to its advantage as another way of assigning blame to smokers for their illnesses.24 In 1986, Congress passed the Comprehensive Smoking Education Act, which required rotating warning labels that were phrased unequivocally linking smoking with particular diseases.25In the 1970s, after warning labels were imposed and both governmental agencies and voluntary health organizations had committed massive resources to educating the public about the dangers of smoking, responsibility for avoiding smoking-related illness was generally viewed as a matter of individual responsibility.12 Tipping the scales further in that direction was a growing sentiment in US society that escalating health care costs could only be contained if individuals changed their unhealthy behavior.26 Pushing back against these forces was the effort by public health advocates to highlight the dangers of secondhand smoke, with the result that “the hazards of smoking were relocated from the individual’s risky behavior to that of his or her smoking neighbor, [and] exposure was no longer a matter of choice but was involuntary victimization.”12^(p339) Thus, the onus shifted once more toward government regulation to ban public smoking, with a concomitant call for businesses to ban smoking in their premises in the absence of governmental action. Up to this point, the tobacco industry had largely escaped accountability by either the public or government despite wide recognition and acceptance of cigarettes’ causal responsibility for disease and death.24The tobacco industry’s use of explicit personal responsibility rhetoric reached its height in the 1980s, during a wave of consumer litigation in which the tobacco defendants countered injured smokers’ lawsuits with claims that ultimately the responsibility for the consequences of smoking cigarettes belonged to the smoker who voluntarily consumed them.27 As the 1990s began, particularly negative pressure was brought to bear on the industry when whistleblowers began leaking internal corporate documents that showed a clear conspiracy to produce an addictive product while ignoring the health hazards of which the tobacco companies were well aware, thus confirming corporate responsibility for the harm the industry’s products caused.9,28,29 As a result of the document leaks and in the face of increasing public demand for industry accountability, many of the industry’s usual allies in business and government began to abandon its cause.This led to a flood of litigation against the industry. Cases brought by state attorneys general seeking Medicaid reimbursement for smoking-related illnesses culminated in the 1998 Master Settlement Agreement.29,30 In the late 1990s and into the 2000s, several juries found in favor of injured smokers in private litigation, with damages being awarded in the millions and even billions of dollars.31 These types of cases continue to be litigated, primarily in Florida, where a jury in a class action found the tobacco industry liable, setting the stage for thousands of individual claims.32,33 Despite continuing to use personal responsibility arguments in smokers’ litigation,34 currently the tobacco defendants are losing about two thirds of the Florida cases, with the juries apportioning responsibility between the plaintiff and the defendant in each case.35Adding to existing scholarship, we sought a deeper understanding of the tobacco industry’s framing, rhetoric, and tactics, and their application, based on both content and legal analyses. Our first study examined the early debate about tobacco and the initial scientific revelations that it was harmful (from 1952 to 1965) and found an unexpected lack of personal responsibility rhetoric by any of the speakers but rather an emphasis on the government’s responsibility to address the issue, which culminated in the passage of the FCLAA.24 Our next study focused on determining when the debate shifted and the tobacco industry began explicitly referring to smokers’ individual personal responsibility, which we found began in the 1970s and gained prominence in the late 1980s, during what has been called the “second wave” of tobacco litigation.27In our study, we examined the specific rhetoric used by the tobacco industry to frame personal responsibility arguments in both the media and the courtroom, and analyzed how the 2 influenced each other. This study’s findings have application not only for tobacco control advocates, but also for others focusing on public health issues arising from the consumption of numerous other products that cause avoidable noncommunicable disease and death, such as obesogenic food and beverages,16,36 alcohol,37 electronic gambling machines,38 and firearms,39 because those industries are now replicating and refining successful tobacco industry tactics and rhetoric. Comprehension of the evolution and cross-pollination of corporate litigation and communications strategy and a focus on corporate malfeasance and deceit will furnish public health advocates with ammunition for developing countermarketing strategies to denormalize health-compromising products and the industries that produce them.40–42     

Pathways to Early Violent Death: The Voices of Serious Violent Youth Offenders

Quantitative studies have uncovered factors associated with early violent death among youth offenders detained in the juvenile justice system, but little is known about the contextual factors associated with pathways to early violent death among youths detained in adult jails.We interviewed young Black male serious violent youth offenders detained in an adult jail to understand their experience of violence. Their narratives reveal how the code of the street, informal rules that govern interpersonal violence among poor inner-city Black male youths, increases the likelihood of violent victimization.Youth offenders detained in adult jails have the lowest rate of service provision among all jail populations. We have addressed how services for youth offenders can be improved to reduce the pathways to early violent death.

“I carry my gun anywhere I go, I mean if I got to crush [kill or injure] someone, then I will. I don’t care. It’s either him or me.”—Ice, aged 17 years

On any given day in the United States 7600 youths younger than 18 years are detained in adult jails.1,2 Youths of color are overrepresented among this group.3 Although they represent only 17% of the total youth population, 62% of youths prosecuted in the adult criminal justice system are Black, and they are 9 times more likely than are White youths to receive an adult prison sentence.4 Serious minority male offenders are more likely to be transferred to adult court and confined to more restrictive settings.5 Research on serious violent youth offenders who were adjudicated in an adult criminal court suggests that they are at greater risk for violent injury and early violent death than are youths processed in juvenile court.6–11 Youths placed in adult jails and prisons are also at greater risk to be sexually and physically assaulted. They are the easiest prey for violent victimization and sexual abuse and so are the hardest hit,12,13 and according to the Centers for Disease Control and Prevention, they are approximately 34% more likely than are youths adjudicated in the juvenile justice system to be rearrested for a violent crime.14Although studies have documented early violent death among youth offenders detained in adult jail,6 a critical omission in this research is contextual information on why the rate of violence and homicide is so high among this population.6,10,11,15–18 Their “voices” are missing.18 Although there is a wealth of quantitative data on risk factors for early violent death among youth offenders,6 we know little about the meaning of violence in their lives and how violence shapes their social worlds. We have addressed this gap in the literature.To explore pathways to early violent death among serious violent youth offenders, we drew on the narratives of Black male adolescents transferred to adult court. We explored how these youth offenders negotiated the social context of inner-city violence while they were on the “outside.” We asked questions regarding “disrespect” as well as the following questions: Did they carry firearms? In what situations would they use a firearm? What role does violence play in their lives? How do drugs, alcohol, and violence fit into the social context of their lives and the communities where they reside? Were they chronically exposed to violence? Have they ever been violently victimized? How do they negotiate violence in the context of jail?     

The Effect of Local Violence on Children’s Attention and Impulse Control

Objectives. We examined whether the burden of violence in a child’s community environment alters the child’s behavior and functioning in the classroom setting.Methods. To identify the effects of local violence, we exploited variation in the timing of local homicides, based on data from the Chicago Police Department, relative to the timing of interview assessments conducted as part of a randomized controlled trial conducted with preschoolers in Head Start programs from 2004–2006, the Chicago School Readiness Project. We compared children’s scores when exposed to recent local violence with scores when no recent violence had occurred to identify causal effects.Results. When children were assessed within a week of a homicide that occurred near their home, they exhibited lower levels of attention and impulse control and lower preacademic skills. The analysis showed strong positive effects of local violence on parental distress, providing suggestive evidence that parental responses may be a likely pathway by which local violence affects young children.Conclusions. Exposure to homicide generates acute psychological distress among caregivers and impairs children’s self-regulatory behavior and cognitive functioning.As one of the leading causes of death among young people, interpersonal violence is an urgent public health problem.1,2 Violence has a disproportionate impact on children, it is highly concentrated in space, and a great deal of evidence suggests that the effects of violence extend beyond the direct victims of assaults or homicides. Direct and indirect exposure to violence is associated with negative health consequences and psychobiological symptoms of distress, such as posttraumatic stress disorder, depression, and difficulty concentrating.3–6 Furthermore, the threat or the experience of violence during childhood can induce high levels of stress, which manifests itself in children’s compromised cognitive functioning, as well as in their academic performance, emotional responses, and social interactions.7–13We considered how the burden of violence in a child’s community can alter the child’s behavior and functioning in the classroom setting. We specifically focused on violence exposure among young children facing socioeconomic disadvantage. Research over the past 2 decades has highlighted stark poverty-related disparities in children’s school readiness as early as kindergarten entry and has underscored poor children’s much higher likelihood of exposure to a wide range of stressful life events, including neighborhood violence.14–17 Yet exposure to violence remains a relatively unexplored pathway through which poor children’s opportunities for learning may be compromised. In examining this pathway, we hypothesized that exposure to extreme community violence, in the form of local homicides, would have an acute impact on children’s ability to regulate behavior, maintain attention, and control impulses in the classroom setting. If local violence affects behavior and performance in the classroom, the results would provide evidence for an additional mechanism by which the problem of community violence extends into key domains of social life, with consequences that have the potential to alter educational trajectories and a range of subsequent health and social outcomes.18–20However, identifying the causal impact of community violence on children’s behavioral and cognitive functioning is difficult because families do not randomly select into violent (or nonviolent) environments.7,21,22 Associations between community violence and children’s outcomes may be a result of unobserved characteristics of families that lead some families to be at higher risk for having to move into (or not being able to move out of) violent community settings.19,23 Those same unobserved parental characteristics may also place children’s likelihood of school success in jeopardy.To address this problem, we departed from the traditional approach to identifying the impact of community violence on children, which involves making comparisons among children living within different communities. Instead, we exploited variation in the timing of local violence—in this case, homicide—relative to the timing of assessments conducted as part of a randomized controlled trial, the Chicago School Readiness Project (CSRP).24,25 The CSRP was designed to assess the effects of a classroom intervention geared toward improving self-regulation and cognitive skills among a sample of students in Head Start classrooms in Chicago. Using data from the CSRP merged with data on homicides across Chicago, we hypothesized that exposure to recent homicides occurring within close geographic proximity to children’s homes affects children’s ability to maintain focus, control impulses, and perform well on tests of preacademic cognitive skills.     

Student Attitudes Toward Concealed Handguns on Campus at 2 Universities

We examined student support for a policy that would allow carrying of concealed handguns on university campuses. Large percentages of students at 2 universities expressed very low levels of comfort with the idea of permitting concealed handgun carrying on campus, suggesting that students may not welcome less restrictive policies. Students held slightly different opinions about concealed handguns on and off campus, suggesting that they view the campus environment as unique with respect to concealed handgun carrying.In response to shootings on college campuses, several states have considered legislation that would allow individuals possessing a concealed handgun license to carry concealed handguns on campus.1 In Texas, a bill allowing licensed individuals to carry concealed handguns on campus passed the state senate in May 2011 but was struck down in a procedural move in the house.2Some research has measured the general public’s opinions about the presence of concealed handguns at universities.3,4 A few studies have also characterized gun carrying among college students, with results showing that students carrying guns are more likely to be male and White, to engage in binge drinking and risky behaviors, to be in trouble with the police, and to attend college in the southern and mountain states.5–7 With the exception of binge drinking and risky behaviors, which have only recently been linked to gun ownership and carrying,8 these results generally conform to studies of guns among other populations in the country.9–18 However, research on college students’ views on gun control is exceedingly rare.19     

Venue-Mediated Weak Ties in Multiplex HIV Transmission Risk Networks Among Drug-Using Male Sex Workers and Associates

Objectives. We investigated the structural characteristics of a multiplex HIV transmission risk network of drug-using male sex workers and their associates.Methods. Using a sample of 387 drug-using male sex workers and their male and female associates in Houston, Texas, we estimated an exponential random graph model to examine the venue-mediated relationships between individuals, the structural characteristics of relationships not linked to social venues, and homophily. We collected data in 2003 to 2004. The network comprised social, sexual, and drug-using relationships and affiliations with social venues.Results. Individuals affiliated with the same social venues, bars, or street intersections were more likely to have nonreciprocated (weak) ties with others. Sex workers were less likely than were other associates to have reciprocated (strong) ties to other sex workers with the same venues. Individuals tended to have reciprocated ties not linked to venues. Partner choice tended to be predicated on homophily.Conclusions. Social venues may provide a milieu for forming weak ties in HIV transmission risk networks centered on male sex workers, which may foster the efficient diffusion of prevention messages as diverse information is obtained and information redundancy is avoided.Sex work increases the risk of contracting and transmitting HIV and other sexually transmitted infections through unprotected sexual behaviors or substance use.1 Male sex workers (MSWs) experience high rates of HIV infection, both globally and domestically.2–4 In North America, HIV prevalence among MSWs is estimated to range from 5% to 31%.4 MSWs have high rates of risky sexual behavior and substance use, including drug injection.5–7 However, public health issues related to MSWs have been understudied, and current HIV prevention programs underserve MSWs.4MSWs are not homogeneous nor are the contexts of male sex work uniform.4,8 Because male sex work takes diverse forms in a variety of contexts,8,9 HIV risks may also vary by context. MSWs who solicit sex on the streets are at high risk for HIV infection, and the context of the street may increase the risk. MSWs working in street venues are more likely to have few financial resources, be undereducated, live in unstable housing or on the streets, be unemployed or disabled, and engage in sex work as a means of survival.8 Numerous MSWs and their clients self-identify as heterosexual.10 Men who have sex with men and women (MSMW) have higher rates of both transactional sex and concurrent illicit drug use and sex than do men who have sex with men only, and, among MSMW, both transactional sex and concurrent illicit drug use predict risky sexual behavior.11Although sociodemographic characteristics, HIV infection, and risk behaviors of MSWs have been documented,12,13 relatively few studies have provided a relational account of HIV risk within male sex work networks. It is known, for example, that networks of MSWs are connected to networks of other high-risk groups.2,8,10,14,15 Through these network ties, MSWs may bridge with men who have sex with men (MSM), female sex workers, drug users, and other less risky groups.2,16 MSMW are more likely to engage in sex for drugs or money than are other MSM, and MSMW occupy a central position in the network of HIV-infected males.17 However, because of the diversity of male sex work, it may be inappropriate to conceptualize MSWs as a core group.18Social networks are the structures within which norms are developed and implemented and social support occurs.19,20 Most risk-potential linkages within networks are social,20 and sex ties are often formed through social circles.21 MSWs form unique social networks,9,22 most likely involving risky drug-use and sexual behaviors. The networks are often hierarchical structures in which network leaders control areas for soliciting sex, and the network structure provides mutual support for soliciting sex.9Rarely do studies on HIV risk networks that involve MSWs regard the network as composed of “persons, places, and the relevant links connecting them.”23^(p684) Social venues are an important part of the network structure, forming the setting for MSWs’ social life and facilitating the formation of “sexual affiliation networks.”24 Our previous study25 underscored the duality of people and places26 by focusing on affiliation networks between MSWs and social venues. We found centralized affiliation patterns around a small number of highly interdependent venues. Although interdependent, the venues presented distinct patterns of venue-based clustering.25 These findings, however, were limited because the study focused on venue affiliation. Non–venue-based direct ties also may be important because they are expected to occur within social, drug-using, and sexual relationships. These types of relationships may have different emotional and interpersonal contexts27 that would tend to result in different patterns and types of ties.We defined a multiplex transmission risk network as composed of multifaceted social contexts that comprise a mix of social, sexual, and drug-using ties and affiliation ties to social venues. The social network perspective informs relational mechanisms of information diffusion and social influence at the entire network and personal network levels. Granovettor’s theory of the strength of weak ties posits, “The weak tie between ego and his acquaintance, therefore, becomes not merely a trivial acquaintance tie but rather a crucial bridge between the two densely knit clumps of close friends.”28^(p202) Weak ties avoid information redundancy by enabling individuals to access diverse information and to facilitate the diffusion of information throughout the entire network.29 Although weak ties facilitate information diffusion, they may not be sufficiently powerful to change behavior because of the ties’ transient and passive nature.Rarely have network studies focused on the role that affiliation ties play in forming direct ties between individuals. We defined venue-mediated weak or strong ties as 1-mode social, sexual, and drug-using ties formed through jointly affiliating in the same venues. We examined and statistically tested local relational features of venue-mediated weak or strong ties among MSWs and their associates. On the basis of the effect of bar-based social influence interventions led by opinion leaders on HIV risk reduction,30,31 HIV prevention messages disseminated within venues are expected to facilitate the diffusion of information, and, thus, weak ties are more likely than are strong ties to be observed linked to social venues.In personal networks, reciprocated ties suggest higher levels of trust and intimacy and, in some cases, a strong tendency to engage in risky behaviors.32 The risk of engaging in behaviors that transmit HIV are also heightened during sex for money exchanges, particularly if there is a strong economic incentive for doing so. This suggests that risk is related to the multiple types of ties determined by context. Additionally, homophily affects network ties by influencing the information that people receive, the attitudes formed, and the social interactions experienced.33 We also sought to examine the tendency of reciprocity and the effect of homophily on HIV status and sociodemographic and behavioral factors when forming risk-potential relationships that comprise social, sexual, or drug-using ties but are not linked to social venues. The likelihood of engaging in risk-taking behavior is greater in relationships with a high degree of homophily, as information flows and persuasion tend to be more frequent among like pairs.32 We tested these relational features using a stochastic network modeling approach.     

Latino Population Growth and Hospital Uncompensated Care in California

Objectives. We examined the association between the size and growth of Latino populations and hospitals’ uncompensated care in California.Methods. Our sample consisted of general acute care hospitals in California operating during 2000 and 2010 (n = 251). We merged California hospital data with US Census data for each hospital service area. We used spatial analysis, multivariate regression, and fixed-effect models.Results. We found a significant association between the growth of California’s Latino population and hospitals’ uncompensated care in the unadjusted regression. This association was still significant after we controlled for hospital and community population characteristics. After we added market characteristics into the final model, this relationship became nonsignificant.Conclusions. Our findings suggest that systematic support is needed in areas with rapid Latino population growth to control hospitals’ uncompensated care, especially if Latinos are excluded from or do not respond to the insurance options made available through the Affordable Care Act. Improving availability of resources for hospitals and providers in areas with high Latino population growth could help alleviate financial pressures.Uncompensated hospital care for the uninsured and underinsured imposes a significant financial burden on the US health care system. The American Hospital Association reported that uncompensated care rose to $45.9 billion in 2012, which accounted for 6.1% of total hospital expenses that year.1 This problem affects hospitals’ financial stability and ability to recoup losses from reduced payments, which in turn can hurt their ability to care for the local population, operate emergency department and specialty services to meet patient needs, and maintain optimal nurse staffing ratios.2–4Hospitals have typically responded to increased uncompensated care by increasing prices for paying patients5; however, Medicaid and Medicare payments have been reduced, and it has become more difficult to shift costs to private payers. Uncompensated care also affects all levels of government, which provide subsidies to offset these losses through other programs.6 The largest source of federal funding for uncompensated care—Medicaid Disproportionate Share Hospital (DSH) payments—totaled $11.4 billion in 2012.7 Despite these mechanisms that indirectly subsidize hospitals’ provision of uncompensated care, hospital closures have been linked to uncompensated care.8Hospital administrators, policymakers, and advocates for the uninsured hoped that the Patient Protection and Affordable Care Act (ACA) would provide health insurance to many of the almost 50 million previously uninsured Americans and thereby significantly reduce uncompensated care. The Supreme Court’s decision on the ACA allows states to opt out of the mostly federally funded Medicaid expansion, which will likely lower the projected numbers of Americans who obtain coverage and potentially undermine the predicted decreases in future uncompensated care by hospitals.9 Existing policy efforts focus on decreasing hospital payments to reduce health care spending,10 and DSH payments are being reduced in anticipation of increases in insurance coverage in all states.11 These recent health policy developments have brought the problem of uncompensated hospital care into a new focus, generating increasing interest in understanding what factors affect hospitals’ financial stress.Some have suggested that immigrants use large amounts of uncompensated care,12 potentially implicating the Latino population—the nation’s largest immigrant group13—in rising uncompensated care. However, hospital uncompensated care may also decrease because of Latinos’ low health care utilization14–21 and expenditures,22–25 which have been described in the context of the healthy immigrant effect (i.e., Latino immigrants are usually younger and healthier than Latinos born in the United States)26 and other factors (e.g., fewer available health care resources, lack of linguistically appropriate care, discrimination in health care settings, and fear of deportation among undocumented Latinos).27,28 Empirical evidence for the potential impact of changing Latino demographics on hospitals’ uncompensated care is limited at best. A study of Oregon state data found weak evidence of an association between the size of the Latino population and hospital uncompensated care.27 A nonsignificant relationship might have reflected Latinos’ immigrant status, limited health care access, and unwillingness or inability to seek health care.California’s hospitals account for more than 10% of uncompensated care nationally.29 California has the largest Latino population of any state, as well as the largest growth rate in its Latino population.29 In 2012, 44.5% of California''s uninsured population was Latino.30 Among the uninsured Latino population in the state, more than 1 million will remain uninsured, even after the ACA’s coverage expansions.31,32 Although some are able to temporarily access emergency Medicaid services for significant, emergent health issues, the majority are uninsured and require help from local indigent care programs, hospital charity care, federally qualified health centers, or other safety net providers. Hence, California, because of its high number (7 million) and percentage (20%) of uninsured residents prior to the ACA,33 offers an excellent setting to study the impact of the Latino population on the uninsured rate, uncompensated care need, and local safety net providers.We examined the association between Latino population growth rates and hospitals’ uncompensated care in California between 2000 and 2010. These growth rates not only reflected the marginal increases in uncompensated care and Latino population estimates, but also took into account baseline levels of these variables. Because growth rates are considered to be better than the level measures for predicting future population growth trends,34 our findings could have important policy implications regarding the allocation of health care resources.     

Trends in Bullying,Physical Fighting,and Weapon Carrying Among 6th- Through 10th-Grade Students From 1998 to 2010: Findings From a National Study

Objectives. We examined trends from 1998 to 2010 in bullying, bullying victimization, physical fighting, and weapon carrying and variations by gender, grade level, and race/ethnicity among US adolescents.Methods. The Health Behavior in School-Aged Children surveys of nationally representative samples of students in grades 6 through 10 were completed in 1998 (n = 15 686), 2002 (n = 14 818), 2006 (n = 9229), and 2010 (n = 10 926). We assessed frequency of bullying behaviors, physical fighting, and weapon carrying as well as weapon type and subtypes of bullying. We conducted logistic regression analyses, accounting for the complex sampling design, to identify trends and variations by demographic factors.Results. Bullying perpetration, bullying victimization, and physical fighting declined from 1998 to 2010. Weapon carrying increased for White students only. Declines in bullying perpetration and victimization were greater for boys than for girls. Declines in bullying perpetration and physical fighting were greater for middle-school students than for high-school students.Conclusions. Declines in most violent behaviors are encouraging; however, lack of decline in weapon carrying merits further attention.Youth violence is a major public health concern.1,2 Even violence that does not lead directly to morbidity or mortality may have mental health consequences.3,4 Three prominent indicators of youth violence are bullying at school, physical fighting, and weapon carrying. These violent behaviors are associated with a number of negative behavioral and emotional outcomes that can last into adulthood.5–10 A recent meta-analysis of longitudinal studies found bullying perpetration and victimization were both related to involvement in violence in the future.8 Bullying and being a victim of bullying have also been found to predict depression and criminal offenses later in life.5,7 A prospective longitudinal twin study in England found that frequent bullying victimization in childhood increased risk of self-harm.11 Finally, a meta-analysis found that both victimized bullies and victims had higher risk for psychosomatic problems (such as aches, sleeping problems, poor appetite, bedwetting, and feeling tense) than noninvolved children.6In cross-sectional studies, physical fighting and weapon carrying have been associated with an increased likelihood of injury that required medical attention.12 Physical fighting has also been concurrently associated with mental health problems, substance use, school adjustment problems, and violent crime.10 Similarly, correlates of weapon carrying include substance use13–15 and property offenses.16The national Youth Risk Behavior Surveillance Survey (YRBS) biennially assesses violent behaviors among 9th- through 12th-grade students. Bullying has only been assessed since 2009 and is limited to having been a victim of bullying on school property or having been bullied electronically. There has been no change in bullying victimization from 2009 to 2011.17 Physical fighting and weapon carrying have been assessed since 1991. Physical fighting declined from 1991 to 2009, with no significant change from 2009 to 2011.17 Weapon carrying declined from 1991 to 1999 but there has been no significant decrease since 1999.17 Other than YRBS, there has been only 1 other nationally representative study of trends in violent behavior in the United States. Molcho et al.18 examined trends in bullying and victimization in 11-, 13-, and 15-year-old adolescents in 27 European countries and the United States from 1994 to 2006 (only from 1998 to 2006 in the United States). They found a significant decrease in all measures of bullying (occasional and chronic victimization and bullying) among boys in the United States but no change among girls. However, they did not examine violent behaviors other than bullying and the sample was not adequate for testing differences in trends by characteristics other than gender.No studies to date have presented trends in bullying, being the victim of a bully (hereafter referred to as victimization), physical fighting, and weapon carrying among US students before high school. The current study expands on the work by Molcho et al.18 by examining more indicators of violent behavior in students aged 11 through 16 years with samples adequate for examining racial/ethnic, gender, and school-grade differences through 2010. It also expands on the YRBS data17 by including students in grades 6 through 8 (as young as 11 years), more waves of data when assessing trends in bullying and bullying perpetration, and testing for differences in trends by gender, race/ethnicity, and grade in school. Little is known about trends in violent behaviors among younger adolescents, where bullying is more prevalent.19 The 2 objectives of the current study were (1) to examine the trends in prevalence of bullying, physical fighting, and weapon carrying in US children and adolescents from grades 6 through 10 spanning 12 years (1998–2010); and (2) to test for variations by gender, grade, and race/ethnicity.     

Avoiding Violent Victimization Among Youths in Urban Neighborhoods: The Importance of Street Efficacy

Objectives. We investigated how street efficacy—the perceived ability to avoid dangerous and unsafe situations—is related to violent victimization across different levels of neighborhood disadvantage.Methods. We used 2 waves of self-report data collected between 1995 and 1999 from 1865 youths in the 9-, 12-, and 15-year-old cohorts of the Project on Human Development in Chicago Neighborhoods to measure violent victimization, street efficacy, and risk factors for violent victimization. We also analyzed data from the 1990 US Census to measure categories of neighborhood concentrated disadvantage for which the cohorts of youths reside. We used logistic regression models to examine the association between street efficacy and violent victimization while we controlled for demographic, family and parenting, self-control, and behavioral and lifestyle variables.Results. Logistic regression results showed that street efficacy had its strongest association with violent victimization in the most disadvantaged neighborhoods (odds ratio = 0.700; 95% confidence interval = 0.55, 0.89).Conclusions. Our findings support the need to teach youths ways to successfully navigate potentially violent situations in environments that pose moderate to high risks for exposure to violence.The violent victimization of youths is of great public concern, when one considers the high rates of exposure to violence faced by youths and the many negative consequences that can follow from victimization. The National Crime Victimization Survey reports that young people aged 12 to 18 years are at the highest risk of becoming victims of violence,1 and the 2007 National Survey of Children’s Exposure to Violence found that more than 60% of youths aged 0 to 17 years were exposed to some violence in the past year, with 39% reporting 2 or more episodes of violence directed toward them.2 Research has also shown that exposure to violence can lead to severe, long-lasting, and diverse problems, including impairment of social relationships, poor academic performance, mental health problems, drug use and abuse, aggression, and violence.3–7A growing body of research has sought to understand the causes and consequences of exposure to community violence experienced by youths in urban environments,8 who are particularly likely to witness or hear about violence perpetrated against others, and to personally experience violence perpetrated by strangers, acquaintances, and peers.4,8–12 Although important in drawing attention to this social problem, with a few exceptions,13 most of these studies have neglected how youths living in urban, socially disadvantaged, and violent neighborhoods can reduce their risk of becoming victims of violence. Instead, it is largely assumed that exposure to violence is a routine and inescapable part of growing up in impoverished communities.We challenged this assumption and explored the possibility that adolescents can be efficacious in reducing their exposure to violence in communities. We focused on youths growing up in areas characterized by high rates of poverty, segregation, and social disadvantage because such environments increase the risk of not only exposure to violence, but also delinquency, perpetration of violence, substance use, mental health problems, and cognitive deficits.13–20 Such neighborhoods clearly pose significant threats to the healthy development of children, and more research needs to be directed toward identifying factors that are associated with the harmful effects of residing in high-risk communities.21In fact, it is recognized that some youths are resilient to the risks associated with disadvantaged communities,21–26 but very little research has investigated the potential for individuals living in high-risk communities to avoid threats of violence and victimization.27 Even in the broader victimization literature, there has been little investigation of how an individual might reduce his or her chances of victimization. Yet, the potential for doing so exists. Although youths have little control over where their families reside and little power to change the structural and social conditions of their neighborhoods that lead to violence, they can learn how to navigate potentially dangerous and unsafe situations, even in violent urban environments. According to Sharkey,26 although children can do little to change their “imposed” environment, they can alter their “selected” environment—the people, behavior, activities, and places that comprise their everyday lives—and do so in ways that minimize their exposure to violence.This perspective recognizes that neighborhood residence is influential but not deterministic. Even youths living in disadvantaged neighborhoods have the ability to positively shape their futures by drawing upon their self-efficacy to make wise decisions regarding whom they befriend, which role models they aspire to, which behaviors they choose to engage in, and how to improve their capacity to avoid potentially violent and unsafe encounters. The belief that one can “avoid violent confrontations and find ways to be safe” has been termed “street efficacy” by Sharkey.26 Using data from the Project on Human Development in Chicago Neighborhoods, Sharkey26 found that adolescents with high levels of street efficacy were less likely to select environments conducive to violence; that is, they were less likely to spend time with peers who engaged in delinquency and to perpetrate violent behavior.In our study, we expanded upon Sharkey’s26 work, as well as literature investigating the epidemiology of violent victimization, to understand how individual variation in street efficacy is associated with violent victimization in high-poverty and lower-poverty urban neighborhoods. Although Sharkey’s26 study was important in demonstrating that street efficacy can reduce participation in violent behavior, his research did not examine the association between street efficacy and violent victimization in highly disadvantaged and less-disadvantaged communities. Thus, the study was unable to establish if youths living in the most high-risk neighborhoods, where exposure to violence is typically highest, can still draw upon street efficacy to reduce their risk of becoming victims of violence. Investigation of this issue can help provide insight into strategies that may be used by youths to reduce their overrepresentation as victims.Our study draws upon information from the 1990 US Census and self-reported data from the 9-, 12-, and 15-year-old cohorts participating in the Project on Human Development in Chicago Neighborhoods. We hypothesized that the relationship between street efficacy and violent victimization would be greatest in the most disadvantaged neighborhoods, as rates of violence are more common in these areas and, thus, the need to protect oneself and avoid situations conducive to violence are most salient here. Although youths living in such neighborhoods may be at risk for direct and indirect violent victimization in their homes, the goal of our research was to focus on the relationship between street efficacy and violent victimization that occurs outside the home. To our knowledge, ours is the first study to apply street efficacy to the understanding of risk of violent victimization in urban neighborhoods differing in levels of concentrated disadvantage.     

Community Violence Perpetration and Victimization Among Adults With Mental Illnesses

Objectives. In a large heterogeneous sample of adults with mental illnesses, we examined the 6-month prevalence and nature of community violence perpetration and victimization, as well as associations between these outcomes.Methods. Baseline data were pooled from 5 studies of adults with mental illnesses from across the United States (n = 4480); the studies took place from 1992 to 2007. The MacArthur Community Violence Screening Instrument was administered to all participants.Results. Prevalence of perpetration ranged from 11.0% to 43.4% across studies, with approximately one quarter (23.9%) of participants reporting violence. Prevalence of victimization was higher overall (30.9%), ranging from 17.0% to 56.6% across studies. Most violence (63.5%) was perpetrated in residential settings. The prevalence of violence-related physical injury was approximately 1 in 10 overall and 1 in 3 for those involved in violent incidents. There were strong associations between perpetration and victimization.Conclusions. Results provided further evidence that adults with mental illnesses experienced violent outcomes at high rates, and that they were more likely to be victims than perpetrators of community violence. There is a critical need for public health interventions designed to reduce violence in this vulnerable population.The risk of violence associated with mental illnesses is a topic of research, media coverage, and debate. Research indicates that between 11% and 52% of adults with mental illnesses have been violent within a 12-month period,1–7 and data from the National Comorbidity Survey show that rates of violence for adults with mental illnesses are 2 to 8 times greater than in the general population.8 Other studies show modest but significant relationships between mental illness and violence,3,9,10 even after controlling for substance abuse.11 Although highly publicized cases of violence perpetrated by adults with mental illnesses have highlighted their “dangerousness,” data suggest they experience victimization at rates comparable to or higher than their rates of perpetration.12 Studies show 12-month prevalence rates between 20% and 44%,7,12–15 and indicate the likelihood of experiencing violent victimization is 23 times higher in adults with mental illnesses compared with the general population.12 Despite these findings, there remains a focus on violence perpetration to the neglect of victimization in this vulnerable population.The increased risk of violent outcomes that is associated with mental illnesses represents a substantial public health burden. Violence can be devastating to victims and perpetrators alike, as well as being costly to the public.16,17 In addition to physical injury, violence may precipitate the loss of personal liberty because of incarceration18 or civil commitment,19 require implementation of expensive clinical and risk assessment and management strategies,20 perpetuate the stigma associated with mental illness,21 and disrupt continuity of care.22 Consequently, an understanding of the prevalence and nature of community violence—both perpetration and victimization—among adults with mental illnesses is critical to public health research and practice.Unfortunately, the empirical literature is limited. First, there are many more studies of perpetration than victimization; a review of the literature found 3 times as many publications about the link between mental illness and violence compared with the link between mental illness and victimization.23 Second, although they are risk factors for each other,24–26 there have been few studies of community violence perpetration and victimization. Only a handful of peer-reviewed publications report on both outcomes in the same sample of adults with mental illnesses during the same reference period.27–30 Third, studies that have examined both outcomes have restricted power and generalizability because of the relatively small, nonrepresentative samples. Fourth, there is heterogeneity in the operational definitions of violence, preventing meaningful comparisons or aggregation of findings. Fifth, violent outcomes are frequently measured with a single yes or no question (e.g., “Have you been victimized in the past 12 months?”), a measurement approach with limited sensitivity.31