Purpose Unaccompanied youth homelessness is a serious concern. Response, however, has been constrained by the absence of credible data on the size and characteristics of the population and reliable means to track youth homelessness over time. We sought to address these gaps. Methods Using a nationally representative phone-based survey (N = 26,161), we solicited household and individual reports on different types of youth homelessness. We collected household reports on adolescents aged 13–17 and young adults aged 18–25, as well as self-reports from young adults aged 18–25. Follow-up interviews with a subsample (n = 150) provided additional information on youth experiences and enabled adjustment for inclusion errors. Results Over a 12-month period, approximately 3.0% of households with 13- to 17-year-olds reported explicit youth homelessness (including running away or being asked to leave) and 1.3% reported experiences that solely involved couch surfing, resulting in an overall 4.3% household prevalence of any homelessness, broadly defined. For 18- to 25-year-olds, household prevalence estimates were 5.9% for explicitly reported homelessness, 6.6% for couch surfing only, and 12.5% overall. The 12-month population prevalence estimates, available only for 18- to 25-year-olds, were 5.2%, 4.5%, and 9.7%, respectively. Incidence rates were about half as high as prevalence rates. Prevalence rates were similar across rural and nonrural counties. Higher risk of homelessness was observed among young parents; black, Hispanic, and lesbian, gay, bisexual, or transgender (LGBT) youth; and those who did not complete high school. Conclusions The prevalence and incidence of youth homelessness reveal a significant need for prevention and youth-centric systems and services, as well as strategies to address disproportionate risks of certain subpopulations.

Importance: The All of Us Research Program hypothesizes that accruing one million or more diverse participants engaged in a longitudinal research cohort will advance precision medicine and ultimately improve human health. Launched nationally in 2018, to date All of Us has recruited more than 345,000 participants. All of Us plans to open beta access to researchers in May 2020. Objective: To demonstrate the quality, utility, and diversity of the All of Us Research Programs initial data release and beta launch of the cloud-based analysis platform, the cloud-based Researcher Workbench. Evidence: We analyzed the initial All of Us data release, comprising surveys, physical measurements (PM), and electronic health record (EHR) data, to characterize All of Us participants including self-reported descriptors of diversity. Data depth, density, and quality were evaluated using medication sequencing analyses for depression and type 2 diabetes. Replication of known oncologic associations with smoking exposure ascertained by EHR and survey data and calculation of population-based atherosclerotic cardiovascular disease risk scores demonstrated the utility of data and platform capability. Findings: The beta launch of the All of Us Researcher Workbench contains data on 224,143 participants. Seventy-seven percent of this cohort were identified as Underrepresented in Biomedical Research (UBR) including over forty-eight percent self-reporting non-White race. Medication usage patterns in common diseases depression and type 2 diabetes replicated prior findings previously reported in the literature and showed differences based on race. Oncologic associations with smoking were replicated and effect sizes compared for EHR and survey exposures finding general agreement. A cardiovascular disease score was calculated utilizing multiple data elements curated across sources. The cloud-based architecture built in the Researcher Workbench provided secure access and powerful computational resources at a low cost. All analyses have been made available for replication and reuse by registered researchers. Conclusions and Relevance: The All of Us Research Programs initial release of cohort data contains longitudinal and multidimensional data on diverse participants that replicate known associations. This dataset and the cloud-based Researcher Workbench advance the mission of All of Us to make data widely and securely available to researchers to improve human health and advance precision medicine.

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