Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease (Nov 2024)

Optimal Instruments for Measurement of Dietary Intake, Physical Activity, and Sleep Among Adults in Population‐Based Studies: Report of a National Heart, Lung, and Blood Institute Workshop

  • Gabriel Anaya,
  • Kelley Pettee Gabriel,
  • Marie‐Pierre St‐Onge,
  • Linda V. van Horn,
  • Alfonso Alfini,
  • Sylvia E. Badon,
  • Carol Boushey,
  • Alison Brown,
  • Christopher M. Depner,
  • Keith M. Diaz,
  • Aiden Doherty,
  • Erin E. Dooley,
  • Dorothea Dumuid,
  • Julio Fernandez‐Mendoza,
  • Michael A. Grandner,
  • Kirsten A. Herrick,
  • Frank B. Hu,
  • Kristen L. Knutson,
  • Amanda Paluch,
  • Charlotte A. Pratt,
  • Jared P. Reis,
  • Jennifer Schrack,
  • Marissa M. Shams‐White,
  • Diana Thomas,
  • Katherine L. Tucker,
  • Maya K. Vadiveloo,
  • Dana L. Wolff‐Hughes,
  • Yuling Hong

DOI
https://doi.org/10.1161/JAHA.124.035818
Journal volume & issue
Vol. 13, no. 21

Abstract

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The National Heart, Lung, and Blood Institute convened a virtual workshop in September 2022 to discuss “Optimal Instruments for Measurement of Diet, Physical Activity, and Sleep.” This report summarizes the proceedings, identifying current research gaps and future directions for measuring different lifestyle behaviors in adult population‐based studies. Key discussions centered on integrating report‐based methods, like questionnaires, with device‐based assessments, including wearables and physiological measures such as biomarkers and omics to enhance self‐reported metrics and better understand the underlying biologic mechanisms of chronic diseases. Emphasis was placed on the need for data harmonization, including the adoption of standard terminology, reproducible metrics, and accessible raw data, to enhance the analysis through artificial intelligence and machine learning techniques. The workshop highlighted the importance of standardizing procedures for integrated behavioral phenotypes using time‐series data. These efforts aim to refine data accuracy and comparability across studies and populations, thereby advancing our understanding of lifestyle behaviors and their impact on chronic disease outcomes over the life course.

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