Effects of School Policies and Programs on Violence Among All High School Students and Sexual and Gender Minority Students

BACKGROUND

Youth identifying as lesbian, gay, bisexual (LGB) and/or transgender/gender nonconforming (TGNC) are at increased risk of violence. School policies and practices may mitigate this risk.

METHODS

Researchers merged data from the 2016 New Mexico School Health Profiles and the 2017 New Mexico Youth Risk and Resiliency Survey. Researchers employed multivariable logistic regression to test the associations between school-level measures and violence outcomes.

RESULTS

Genders and sexualities alliances (GSAs) were associated with reduced odds of lifetime forced sex among all, heterosexual cisgender, and LGB students, reduced odds of sexual violence among heterosexual cisgender students, and reduced odds of dating violence among LGB students. Inclusive sexual health education was associated with reduced odds of lifetime forced sex among LGB and TGNC students, reduced odds of sexual violence among LGB students, and increased odds of dating violence among heterosexual cisgender students. Inclusive teacher training was associated with increased odds of lifetime forced sex among TGNC students.

IMPLICATIONS FOR SCHOOL HEALTH POLICY, PRACTICE, AND EQUITY

Inclusive sexual health education and the presence of active GSAs may have the greatest potential for reducing violence, especially among LGB and TGNC students.

CONCLUSIONS

Findings highlight the important role of school policies and practices in addressing violence.

Proteomic cardiovascular risk assessment in chronic kidney disease

AIMS

Chronic kidney disease (CKD) is widely prevalent and independently increases cardiovascular risk. Cardiovascular risk prediction tools derived in the general population perform poorly in CKD. Through large-scale proteomics discovery, this study aimed to create more accurate cardiovascular risk models.

METHODS AND RESULTS

Elastic net regression was used to derive a proteomic risk model for incident cardiovascular risk in 2182 participants from the Chronic Renal Insufficiency Cohort. The model was then validated in 485 participants from the Atherosclerosis Risk in Communities cohort. All participants had CKD and no history of cardiovascular disease at study baseline when ∼5000 proteins were measured. The proteomic risk model, which consisted of 32 proteins, was superior to both the 2013 ACC/AHA Pooled Cohort Equation and a modified Pooled Cohort Equation that included estimated glomerular filtrate rate. The Chronic Renal Insufficiency Cohort internal validation set demonstrated annualized receiver operating characteristic area under the curve values from 1 to 10 years ranging between 0.84 and 0.89 for the protein and 0.70 and 0.73 for the clinical models. Similar findings were observed in the Atherosclerosis Risk in Communities validation cohort. For nearly half of the individual proteins independently associated with cardiovascular risk, Mendelian randomization suggested a causal link to cardiovascular events or risk factors. Pathway analyses revealed enrichment of proteins involved in immunologic function, vascular and neuronal development, and hepatic fibrosis.

CONCLUSION

In two sizeable populations with CKD, a proteomic risk model for incident cardiovascular disease surpassed clinical risk models recommended in clinical practice, even after including estimated glomerular filtration rate. New biological insights may prioritize the development of therapeutic strategies for cardiovascular risk reduction in the CKD population.