Increasing Representativeness in theAll of UsCohort Using Inverse Probability Weighting

Abstract Large-scale population biobanks rely on volunteer participants, which may introduce biases that compromise the external validity of epidemiological studies. We characterized the volunteer participant bias for the All of Us Research Program cohort and developed a set of inverse probability (IP) weights that can be used to mitigate this bias. The All of Us cohort is older, more female, more likely to have higher education, more likely to be covered by health insurance, less White, less likely to drink or smoke, and less likely to report being healthy compared to the US population. IP weights developed via comparison of a nationally representative database reduced the observed biases for all demographic and lifestyle characteristics. Furthermore, IP weighting corrected for differences in the correlation structure of the data. For all variables we corrected for, IP weighting brought correlation coefficients and pairwise variable associations closer to the nationally representative estimates. We provide our IP weights as a community resource to increase the representativeness and external validity of the All of Us cohort. Competing Interest Statement The authors have declared no competing interest. Funding Statement Open Access funding provided by the National Institutes of Health (NIH) MK, and LMR supported by the Division of Intramural Research of the National Institute on Minority Health and Health Disparities at the National Institutes of Health (Award Number: 1ZIAMD000018) to LMR; National Institutes of Health Distinguished Scholars Program to LMR; SS supported by the Georgia Tech Bioinformatics Graduate Program; JL supported by the Intramural Research Program of the National Institutes of Health, National Library of Medicine, and National Center for Biotechnology Information; and IHRC-Georgia Tech Applied Bioinformatics Laboratory (Award Number: RF383) to IKJ. Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The nationally representative database used to develop weights was the 2017 - March 2020 National Health and Nutrition Examination Survey (NHANES). This data is free to access and publicly available at: https://wwwn.cdc.gov/nchs/nhanes/continuousnhanes/default.aspx?Cycle=2017-2020 The 2021-2023 NHANES sample is also free to access and publicly available at: https://wwwn.cdc.gov/nchs/nhanes/continuousnhanes/default.aspx?Cycle=2021-2023 We used version 7 of the All of Us Controlled Tier Dataset, which can be accessed and analyzed from the Researcher Workbench by registered users: https://www.researchallofus.org/data-tools/workbench/ I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes Footnotes This analysis has been revised to include a more robust weighting method, and focus on correlation structure within the All of Us dataset. We have removed results from GWAS studies and disease prevalence analysis. Data Availability The nationally representative database used to develop weights was the 2017 - March 2020 National Health and Nutrition Examination Survey (NHANES). This data is free to access and publicly available at: https://wwwn.cdc.gov/nchs/nhanes/continuousnhanes/default.aspx?Cycle=2017-2020 The 2021-2023 NHANES sample is also free to access and publicly available at: https://wwwn.cdc.gov/nchs/nhanes/continuousnhanes/default.aspx?Cycle=2021-2023 We used version 7 of the All of Us Controlled Tier Dataset, which can be accessed and analyzed from the Researcher Workbench by registered users: https://www.researchallofus.org/data-tools/workbench/ https://wwwn.cdc.gov/nchs/nhanes/continuousnhanes/default.aspx?Cycle=2017-2020