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Development and validation of mortality prediction models based on the social determinants of health
  1. Khalid Fahoum1,2,
  2. Joanna Bryan Ringel3,
  3. Jana A Hirsch4,
  4. Andrew Rundle5,
  5. Emily B Levitan6,
  6. Evgeniya Reshetnyak3,
  7. Madeline R Sterling3,
  8. Chiomah Ezeoma7,
  9. Parag Goyal3,
  10. Monika M Safford3
  1. 1Weill Cornell Medicine, New York, New York, USA
  2. 2Department of Medicine, NYU Grossman School of Medicine, New York, New York, USA
  3. 3Department of Medicine, Weill Cornell Medicine, New York, New York, USA
  4. 4Urban Health Collaborative, Drexel University School of Public Health, Philadelphia, Pennsylvania, USA
  5. 5Columbia University, New York, New York, USA
  6. 6University of Alabama at Birmingham, Birmingham, Alabama, USA
  7. 7Department of Population Health Sciences, Weill Cornell Medicine, New York, New York, USA
  1. Correspondence to Khalid Fahoum, New York, NY, USA; khalid.fahoum{at}gmail.com

Abstract

Background There is no standardised approach to screening adults for social risk factors. The goal of this study was to develop mortality risk prediction models based on the social determinants of health (SDoH) for clinical risk stratification.

Methods Data were used from REasons for Geographic And Racial Differences in Stroke (REGARDS) study, a national, population-based, longitudinal cohort of black and white Americans aged ≥45 recruited between 2003 and 2007. Analysis was limited to participants with available SDoH and mortality data (n=20 843). All-cause mortality, available through 31 December 2018, was modelled using Cox proportional hazards with baseline individual, area-level and business-level SDoH as predictors. The area-level Social Vulnerability Index (SVI) was included for comparison. All models were adjusted for age, sex and sampling region and underwent internal split-sample validation.

Results The baseline prediction model including only age, sex and REGARDS sampling region had a c-statistic of 0.699. An individual-level SDoH model (Model 1) had a higher c-statistic than the SVI (0.723 vs 0.708, p<0.001) in the testing set. Sequentially adding area-level SDoH (c-statistic 0.723) and business-level SDoH (c-statistics 0.723) to Model 1 had minimal improvement in model discrimination. Structural racism variables were associated with all-cause mortality for black participants but did not improve model discrimination compared with Model 1 (p=0.175).

Conclusion In conclusion, SDoH can improve mortality prediction over 10 years relative to a baseline model and have the potential to identify high-risk patients for further evaluation or intervention if validated externally.

  • MORTALITY
  • PREVENTIVE MEDICINE
  • PUBLIC HEALTH
  • SCREENING

Data availability statement

Data may be obtained from a third party and are not publicly available. The data sets generated during and/or analysed during the current study are not publicly available due to participant privacy concerns. In order to abide by its obligations with NIH/NINDS and the IRB of the University of Alabama at Birmingham, REGARDS facilitates data sharing through formal data use agreements. Any investigator is welcome to request the REGARDS data and documentation through this process. Requests for data access may be sent to the REGARDS study at regardsadmin@uab.edu.

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Data availability statement

Data may be obtained from a third party and are not publicly available. The data sets generated during and/or analysed during the current study are not publicly available due to participant privacy concerns. In order to abide by its obligations with NIH/NINDS and the IRB of the University of Alabama at Birmingham, REGARDS facilitates data sharing through formal data use agreements. Any investigator is welcome to request the REGARDS data and documentation through this process. Requests for data access may be sent to the REGARDS study at regardsadmin@uab.edu.

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Footnotes

  • Contributors KF conceived the study idea, reviewed the literature, developed the analytical plan, interpreted results and led manuscript writing and revisions. JBR developed the analytical plan, conducted all data analysis and provided critical feedback on the manuscript. JAH provided critical input on using key data sources, interpreted results and provided critical feedback on manuscript. AR provided critical input on using key data sources, interpreted results. EBL provided critical input on the analytical plan, oversaw data analysis, interpreted results and provided critical feedback on the manuscript. ER provided critical input on the analytical plan. MRS provided critical input on the study idea and methodology, provided critical feedback on the manuscript. CE provided critical input on the study idea and methodology. PG provided critical input on the study idea and methodology, provided critical feedback on the manuscript. MMS developed the study idea, oversaw all stages of planning and data analysis, interpreted results, provided critical feedback on the manuscript, and is responsible for the overall content as the guarantor.

  • Funding This research project is supported by a cooperative agreement U01 NS041588 from the National Institute of Neurological Disorders and Stroke, National Institutes of Health, Department of Health and Human Service. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute of Neurological Disorders and Stroke or the National Institutes of Health. Representatives of the funding agency have been involved in the review of the manuscript but not directly involved in the collection, management, analysis or interpretation of the data. The authors thank the other investigators, the staff and the participants of the REGARDS study for their valuable contributions. A full list of participating REGARDS investigators and institutions can be found at http://www.regardsstudy.org. Additional funding was provided by investigator-initiated grant R01 HL80477 from the National Heart, Lung and Blood Institute. Representatives from the National Heart, Lung and Blood Institute did not have any role in the design and conduct of the study, the collection, management, analysis and interpretation of the data, or the preparation or approval of the manuscript. Additionally, this work was supported by the National Institute on Aging (grants 1R01AG049970, 3R01AG049970-04S1), Commonwealth Universal Research Enhancement (CURE) programme funded by the Pennsylvania Department of Health - 2015 Formula award - SAP #4100072543, the Urban Health Collaborative at Drexel University and the Built Environment and Health Research Group at Columbia University.

  • Competing interests MMS is the founder and owner of MedExplain, a medical education company. EBL receives research support from Amgen (to her institution, not to her directly). The other authors declare that they have no competing interests.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Citation Abstracts from the 2022 Annual Meeting of the Society of General Internal Medicine. J GEN INTERN MED 37 (Suppl 2), 129–664 (2022). https://doi.org/10.1007/s11606-022-07653-8

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