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Establishing more campus mental health clinics, fostering supportive campus environments, and increasing students' coping skills may reduce unmet need for mental health services among college students.

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Background Opioid analgesic and benzodiazepine use in individuals with opioid use disorders (OUDs) can increase the risk for medical consequences and relapse. Little is known about rates of use of these medications or prescribing patterns among communities of prescribers. Aims To examine rates of prescribing to Medicaid-enrollees in the calendar year after an OUD diagnosis, and to examine individual, county, and provider community factors associated with such prescribing. Methods We used 2008 Medicaid claims data from 12 states to identify enrollees diagnosed with OUDs, and 2009 claims data to identify rates of prescribing of each drug. We used social network analysis to identify provider communities and multivariate regression analyses to identify patient, county, and provider community level factors associated with prescribing these drugs. We also examined variation in rates of prescribing across provider communities. Results Among Medicaid-enrollees identified with an OUD, 45% filled a prescription for an opioid analgesic, 37% for a benzodiazepine, and 21% for both in the year following their diagnosis. Females, older individuals, individuals with pain syndromes, and individuals residing in counties with higher rates of poverty were more likely to fill prescriptions. Prescribing rates varied substantially across provider communities, with rates in the highest quartile of prescribing communities over 2.5 times the rates in the lowest prescribing communities. Discussion Prescribing opioid analgesics and benzodiazepines to individuals diagnosed with OUDs may increase risk of relapse and overdose. Interventions should be considered that target provider communities with the highest rates of prescribing and individuals at highest risk.

ObjectiveTo evaluate the association between racial residential segregation, a prominent manifestation of systemic racism, and the White-Black survival gap in a contemporary cohort of adults, and to assess the extent to which socioeconomic inequality explains this association.DesignThis was a cross sectional study of White and Black men and women aged 35–75 living in 102 large US Core Based Statistical Areas. The main outcome was the White-Black survival gap. We used 2009–2013 CDC mortality data for Black and White men and women to calculate age-, sex- and race adjusted White and Black mortality rates. We measured segregation using the Dissimilarity index, obtained from the Manhattan Institute. We used the 2009–2013 American Community Survey to define indicators of socioeconomic inequality. We estimated the CBSA-level White–Black gap in probability of survival using sequential linear regression models accounting for the CBSA dissimilarity index and race-specific socioeconomic indicators.ResultsBlack men and women had a 14% and 9% lower probability of survival from age 35 to 75 than their white counterparts. Residential segregation was strongly associated with the survival gap, and this relationship was partly, but not fully, explained by socioeconomic inequality. At the lowest observed level of segregation, and with the Black socioeconomic status (SES) assumed to be at the White SES level scenario, the survival gap is essentially eliminated.ConclusionWhite-Black differences in survival remain wide notwithstanding public health efforts to improve life expectancy and initiatives to reduce health disparities. Eliminating racial residential segregation and bringing Black socioeconomic status (SES) to White SES levels would eliminate the White-Black survival gap.