The Structural Violence Trap: Disparities in Homicide, Chronic Disease Death, and Social Factors Across San Francisco Neighborhoods

Living Dead: Trans Cooperations with Mad Necropolitics and the Mad Trans Coalitions that Might Replace Them

Trans subjectivities continue to be included in major compendia of mental illness, despite recent moves to depathologize "cross-gender identification." Regardless, the inclusion of "gender dysphoria" is often framed as a formal mechanism to support access to gender affirming care as transgender subjectivities are re-conceptualized as part of sex/gender diversity and away from madness. The latter permits trans individuals to evade sanist oppressions. However, moves to disassociate from mad individuals also often serve to condone sanism. For instance, a contemporary policy landscape often sees transgender advocates arguing for the "medical necessity" of gender affirming care for gender dysphoria as a "recognized medical condition," thereby skirting the inclusion of gender dysphoria as a psychiatric condition and implying that gender dysphoria carries a special ontological status that separates it from madness (reified as "mental illness"). More though, this framework endorses material violences toward mad individuals that are often advanced via the workings of the state to consign marginalized constituents to death by withholding the means of life, i.e., necropolitics. In the following, I argue that trans disassociations from madness often endorses or assents to mad necropolitics. Drawing from Mbembe's (Necropolitics. Duke University Press, Durham, 2019) framework, I suggest that medicalizing trans narratives, despite being used to object to anti-trans laws in contemporary context, ideologically support mad "death worlds" organized through the U.S.A. welfare state and prison industrial complex. However, I also suggest alternative strategies, i.e., intersectional collaboration, that may uplift mad and/or trans communities.

Medical ambivalence and Long Covid: The disconnects, entanglements, and productivities shaping ethnic minority experiences in the UK

Structural violence - related to 'isms' like racism, sexism, and ableism - pertains to the ways in which social institutions harm certain groups. Such violence is critical to institutional indifference to the plight of ethnic minority people living with long-term health conditions. With only emergent literature on the lived experiences of ethnic minorities with Long Covid, we sought to investigate experiences around the interplay of illness and structural vulnerabilities. Thirty-one semi-structured interviews with a range of UK-based participants of varying ethnic minorities, ages and socio-economic situations were undertaken online between June 2022 and June 2023. A constant comparison analysis was used to develop three over-arching themes: (1) Long Covid and social recognition; (2) The violence of medical ambivalence; and (3) Pathways to recognition and support. Findings showed that while professional recognition and support were possible, participants generally faced the spectre and deployment of a particular mode of structural violence, namely 'medical ambivalence'. The contours of medical ambivalence in the National Health Service (NHS) as an institution had consequences, including inducing or accentuating suffering via practices of care denial. Despite multiple structurally shaped ordeals (like healthcare, community stigma, and sexism), many participants were nevertheless able to gain recognition for their condition (e.g. online, religious communities). Participants with more resources were in the best position to 'cobble together' their own approaches to care and support, despite structural headwinds.

Fatal and Nonfatal Firearm Injury Rates by Race and Ethnicity in the United States, 2019 to 2020

BACKGROUND

Racial disparities in firearm injury death in the United States are well established. Less is known about the magnitude of nonfatal and total firearm injury.

OBJECTIVE

To combine health care data with death certificate data to estimate total firearm injuries in various racial and ethnic groups.

DESIGN

Retrospective, cross-sectional study.

SETTING

Fatal injury data were collected from the Centers for Disease Control and Prevention. Data on nonfatal injuries were collected from the Nationwide Emergency Department Sample (NEDS), a 20% stratified sample of U.S. emergency department visits, weighted to provide national estimates for the United States, 2019 to 2020.

PARTICIPANTS

All firearm injuries and deaths in the United States.

INTERVENTION

Race and ethnicity were classified into 5 mutually exclusive categories: Asian or Pacific Islander, Black, Hispanic, Native American, and White. International Classification of Diseases, 10th Revision codes were used to classify firearm injury intent.

MEASUREMENTS

Incidence of fatal and nonfatal injury in the U.S. population and case-fatality ratios (CFRs).

RESULTS

There were 252 376 total firearm injuries, including 84 908 deaths from firearm injures. Of all firearm injuries, 37.8% were unintentional, 37.3% were assault related, 21.0% were self-harm, and 1.3% were law enforcement associated. Self-harm had the highest CFRs (90.9% overall). Unintentional injuries accounted for just 1021 (1.2%) deaths but 94 433 (56.4%) of nonfatal injuries. Rates of self-harm were highest among White persons (11.0 per 100 000 population in 2020) followed by Native Americans (8.6 per 100 000). Rates of assault were highest among Black persons (70.1 per 100 000), as were unintentional injuries (56.1 per 100 000).

LIMITATION

Findings are limited by the accuracy of discharge coding in NEDS, particularly regarding injury intent and patient race and ethnicity.

CONCLUSION

From 2019 to 2020, the total burden of firearm injuries amounts to an average of 1 injury every 4 minutes and 1 death every 12 minutes in the United States. Racial disparities in firearm injury death are mirrored in nonfatal injury.

PRIMARY FUNDING SOURCE

None.

Serious Mental Illness, Glycemic Control, and Neighborhood Factors within an Urban Diabetes Cohort

BACKGROUND AND HYPOTHESIS

Serious mental illness (SMI) may compromise diabetes self-management. This study assessed the association between SMI and glycemic control, and explored sociodemographic predictors and geographic clustering of this outcome among patients with and without SMI.

STUDY DESIGN

We used electronic health record data for adult primary care patients with diabetes from 2 San Francisco health care delivery systems. The primary outcome was poor glycemic control (hemoglobin A1c >9.0%), which was modeled on SMI diagnosis status and sociodemographics. Geospatial analyses examined hotspots of poor glycemic control and neighborhood characteristics.

STUDY RESULTS

The study included 11 694 participants with diabetes, 21% with comorbid SMI, of whom 22% had a schizophrenia spectrum or bipolar disorder. Median age was 62 years; 52% were female and 79% were Asian, Black, or Hispanic. In adjusted models, having schizophrenia spectrum disorder or bipolar disorder was associated with greater risk for poor glycemic control (vs participants without SMI, adjusted relative risk [aRR] = 1.24; 95% confidence interval, 1.02, 1.49), but having broadly defined SMI was not. People with and without SMI had similar sociodemographic correlates of poor glycemic control including younger versus older age, Hispanic versus non-Hispanic White race/ethnicity, and English versus Chinese language preference. Hotspots for poor glycemic control were found in neighborhoods with more lower-income, Hispanic, and Black residents.

CONCLUSIONS

Poor diabetes control was significantly related to having a schizophrenia spectrum or bipolar disorder, and to sociodemographic factors and neighborhood. Community-based mental health clinics in hotspots could be targets for implementation of diabetes management services.

Neighborhood deprivation and childhood opportunity indices are associated with violent injury among children in Los Angeles County

BACKGROUND

Previous research has demonstrated mixed relationships between individual neighborhood socioeconomic factors and incidences of violence, such as poverty level, population density, and income inequality. We used the Childhood Opportunity Index and Area Disadvantage Index to evaluate the relationship between neighborhood characteristics and the number of incidents of violence among children across the zip codes of Los Angeles (LA) County.

METHODS

We performed a retrospective cross-sectional study of children younger than 18 years from 2017 to 2019 who were entered in the LA County Trauma and Emergency Medicine Information System registry with violent mechanisms of injury, including gunshot, stabbing, or assault. Mechanisms classified as self-inflicted injuries were excluded from the study. The number of incidences of violent mechanism per 100,000 persons younger than 18 years for each zip code was calculated using population data from the US Census American Community Survey 5-Year estimates from 2019. The incidences of violence per capita younger than 18 years for each zip code was compared with the zip code Area Deprivation Index and Childhood Opportunity Index using logistic regression models.

RESULTS

There were 6,791 trauma activations in LA County over the study period, 12.8% (n = 866) of which were due to violence. The mean prevalence of pediatric violent mechanism of injury per zip code was 4 cases per 100,000 persons younger than 18 years. Most injuries were the result of firearms (n = 345 [60.4%]) and occurred among Hispanic/Latino children (n = 362 [57.1%]). There were significantly greater rates of violent injury among children from highest disadvantage (odds ratio, 8.84) and lowest opportunity (odds ratio, 42.48) zip codes.

CONCLUSION

Children living in high disadvantage or low opportunity zip codes had greater rates of violent injury. Further study of neighborhood factors is needed to develop targeted effective interventions to reduce violent injuries among children living in low opportunity areas.

LEVEL OF EVIDENCE

Prognostic and Epidemiological; Level IV.

Study designs, measures and indexes used in studying the structural racism as a social determinant of health in high income countries from 2000-2022: evidence from a scoping review

BACKGROUND

Globally, structural racism has been well documented as an important social determinant of health (SODH) resulting in racial inequality related to health. Although studies on structural racism have increased over the years, the selection of appropriate designs, measures, and indexes of measurement that respond to SODH has not been comprehensively documented. Therefore, the lack of evidence seems to exist. This scoping review was conducted to map and summarize global evidence on the use of various designs, measures, and indexes of measurement when studying structural racism as a social determinant of health.

METHODS

We performed a scoping review of global evidence from 2000 to 2022 published in 5 databases: PubMed, Cumulative Index to Nursing and Allied Health Literature (CINAHL), PsycInfo, Web of Science, ProQuest, and relevant grey literature on structural racism. We conducted a systematic search using keywords and subject headings around 3 concepts. We included peer reviewed original research/review articles which conceived the framework of social determinants of health (SODH) and studied structural racism.

RESULTS

Our review identified 1793 bibliographic citations for screening and 54 articles for final review. Articles reported 19 types of study design, 87 measures of exposure and 58 measures of health outcomes related to structural racism. 73 indexes or scales of measurement were used to assess health impacts of structural racism. Majority of articles were primary research (n = 43/54 articles; 79.6%), used quantitative research method (n = 32/54 articles; 59.3%) and predominantly conducted in the United States (n = 46/54 articles; 85.2.6%). Cross-sectional study design was the most used design (n = 17/54 articles; 31.5%) followed by systematic review (n = 7/54 articles; 13.0%) and narrative review (n = 6/54 articles; 11.1%). Housing and residential segregation was the largest cluster of exposure with the highest impact in infant health outcome.

CONCLUSIONS

Our review found several key gaps and research priorities on structural racism such as lack of longitudinal studies and availability of structural or ecological data, lack of consensus on the use of consolidated appropriate measures, indexes of measurement and appropriate study designs that can capture complex interactions of exposure and outcomes related to structural racism holistically.

Associations Between Adverse Childhood Experiences, Adolescent Screen Time and Physical Activity During the COVID-19 Pandemic

OBJECTIVE

To determine the associations between Adverse Childhood Experiences (ACEs), adolescent screen time, and physical activity during the early COVID-19 pandemic.

METHODS

Data (2016-2020) from the Adolescent Brain Cognitive Development (ABCD) study were analyzed. Linear regression analyses estimated associations between ACE score and screen time and physical activity in May 2020, adjusting for potential confounders.

RESULTS

Of the 6749 adolescent respondents primarily aged 12-13, 81.6% reported a history of one ACE or more. In adjusted models, a higher ACE score was significantly associated with greater hours per day of screen time, with youth with ≥4 ACEs associated with 2.3 more hours of screen time per day compared to youth with 0 ACEs. In addition, the adjusted models found that a higher ACE score was associated with lower physical activity; youth with ≥4 ACEs averaged 0.8 fewer hours per week of physical activity and 0.5 fewer days per week of 60 minutes of physical activity compared to youth with 0 ACEs. Gender and race were also significantly associated with changes in screen time and physical activity.

CONCLUSIONS

ACEs are associated with higher adolescent sedentary behaviors, particularly greater screen time, during the early COVID-19 pandemic (May 2020). Clinicians caring for youth exposed to trauma in the postpandemic environment should explore screen time and physical activity behaviors.