Development of the Initial Surveys for the All of Us Research Program

Cronin, Robert M.; Jerome, Rebecca N; Mapes, Brandy; Andrade, Regina; Johnston, Rebecca; Ayala, Jennifer; Schlundt, David G.; Bonnet, Kemberlee; Kripalani, Sunil; Goggins, Kathryn; Wallston, Kenneth A.; Couper, Mick P.; Elliott, Michael R.; Harris, Paul A.; Begale, Mark; Muñoz, Fátima; Lopez-Class, Maria; Cella, David; Condon, David M; AuYoung, Mona; Mazor, Kathleen M.; Mikita, Steve; Manganiello, Michael; Borselli, Nicholas; Fowler, Stephanie L.; Rutter, Joni L.; Denny, Joshua C.; Karlson, Elizabeth W.; Ahmedani, Brian K.; O’Donnell, Christopher J.

doi:10.1097/ede.0000000000001028

Cited by 48 publications

(34 citation statements)

References 37 publications

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“…Simultaneously expanding prospects for linkage to medical and non-medical electronic records has allowed construction of studies with the capacity to explore the effect of gene-environment combinations on health endpoints at a previously unheralded scale. Several countries have established such national “biobanks,”12 are in the process of their formulation,345 or are planning such an endeavour 6…”

Section: Introductionmentioning

confidence: 99%

Comparison of risk factor associations in UK Biobank against representative, general population based studies with conventional response rates: prospective cohort study and individual participant meta-analysis

Batty

Gale

Kivimäki

et al. 2020

BMJ

450

352

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ObjectiveTo compare established associations between risk factors and mortality in UK Biobank, a study with an exceptionally low rate of response to its baseline survey, against those from representative studies that have conventional response rates.DesignProspective cohort study alongside individual participant meta-analysis of other cohort studies.SettingUnited Kingdom.ParticipantsAnalytical sample of 499 701 people (response rate 5.5%) in analyses in UK Biobank; pooled data from the Health Surveys for England (HSE) and the Scottish Health Surveys (SHS), including 18 studies and 89 895 people (mean response rate 68%). Both study populations were linked to the same nationwide mortality registries, and the baseline age range was aligned at 40-69 years.Main outcome measureDeath from cardiovascular disease, selected malignancies, and suicide. To quantify the difference between hazard ratios in the two studies, a ratio of the hazard ratios was used with HSE-SHS as the referent.ResultsRisk factor levels and mortality rates were typically more favourable in UK Biobank participants relative to the HSE-SHS consortium. For the associations between risk factors and mortality endpoints, however, close agreement was seen between studies. Based on 14 288 deaths during an average of 7.0 years of follow-up in UK Biobank and 7861 deaths over 10 years of mortality surveillance in HSE-SHS, for cardiovascular disease mortality, for instance, the age and sex adjusted hazard ratio for ever having smoked cigarettes (versus never) was 2.04 (95% confidence interval 1.87 to 2.24) in UK Biobank and 1.99 (1.78 to 2.23) in HSE-SHS, yielding a ratio of hazard ratios close to unity (1.02, 0.88 to 1.19). The overall pattern of agreement between studies was essentially unchanged when results were compared separately by sex and when baseline years and censoring dates were aligned.ConclusionDespite a very low response rate, risk factor associations in the UK Biobank seem to be generalisable.

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Section: Introductionmentioning

confidence: 99%

Comparison of risk factor associations in UK Biobank against representative, general population based studies with conventional response rates: prospective cohort study and individual participant meta-analysis

Batty

Gale

Kivimäki

et al. 2020

BMJ

450

352

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“…Including the racial and ethnic groups, Table 1 shows historically represented and underrepresented characteristics of each category and how they are measured by the survey responses. [13] Researchers interested in studying specific subsets of these groups (for example, individuals < 3 or >80), are able to do so based on the way in which these demographic data have been collected.…”

Section: Resultsmentioning

confidence: 99%

Diversity and inclusion for the All of Us research program: A scoping review

et al. 2020

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The All of Us Research Program (All of Us) is a national effort to accelerate health research by exploring the relationship between lifestyle, environment, and genetics. It is set to become one of the largest research efforts in U.S. history, aiming to build a national resource of data from at least one million participants. All of Us aims to address the need for more diversity in research and set the stage for that diversity to be leveraged in precision medicine research to come. This paper describes how the program assessed demographic characteristics of participants who have enrolled in other U.S. biomedical research cohorts to better understand which groups are traditionally represented or underrepresented in biomedical research. We 1) reviewed the enrollment characteristics of national cohort studies like All of Us, and 2) surveyed the literature, focusing on key diversity categories essential to the program's enrollment aims. Based on these efforts, All of Us emphasizes enrollment of racial and ethnic minorities, and has formally designated the following additional groups as historically underrepresented: individuals-with inadequate access to medical care; under the age of 18 or over 65; with an annual household income at or below 200% of the federal poverty level; who have a cognitive or physical disability; have less than a high school education or equivalent; are intersex; identify as a sexual or gender minority; or live in rural or non-metropolitan areas. Research accounting for wider demographic variability is critical. Only by ensuring diversity and by addressing the very barriers that limit it, can we position All of Us to better understand and tackle health disparities.

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“…The first three surveys available immediately at the time of enrollment included “The Basics” (socio-demographic questions), “Overall Health” (general health overview), and “Lifestyle” (tobacco, alcohol, and drug use related questions) 10 . The second set of three surveys are made available 90 days after enrollment and include “Healthcare Access & Utilization” (how participants access and utilize the healthcare system), “Family History” (the participant’s family health history), and “Personal Medical History” (a participant’s medical history).…”

Section: Methodsmentioning

confidence: 99%

The All of Us Research Program: data quality, utility, and diversity

Ramirez

Sulieman

Schlueter

et al. 2020

Preprint

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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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Development of the Initial Surveys for the All of Us Research Program

Abstract: The research assessments described in this manuscript were approved by the Institutional Review Board (IRB) of the All of Us Research Program. Those participants that completed cognitive interview gave oral consent to do so.

Cited by 48 publications

References 37 publications

Comparison of risk factor associations in UK Biobank against representative, general population based studies with conventional response rates: prospective cohort study and individual participant meta-analysis

Comparison of risk factor associations in UK Biobank against representative, general population based studies with conventional response rates: prospective cohort study and individual participant meta-analysis

Diversity and inclusion for the All of Us research program: A scoping review

The All of Us Research Program: data quality, utility, and diversity

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