Poly-metabolite score of adherence to the 2018 World Cancer Research Fund (WCRF)/American Institute for Cancer Research (AICR) Cancer Prevention Recommendations in the Interactive Diet and Activity Tracking in AARP (IDATA) Study |
Erikka Loftfield |
Erikka Loftfield Cronin |
IDATA |
Jun 14, 2024 |
IDATA-74 |
Applying Machine Learning To Assess Dietary Patterns |
Weslie Khoo |
Indiana University |
IDATA |
Apr 11, 2024 |
IDATA-72 |
Predictive Health: Navigating Dietary Dynamics and BMI Trajectories for Chronic Condition Prevention |
Yao-Chi Yu |
Tarleton State University |
IDATA |
Apr 11, 2024 |
IDATA-70 |
Comparison of net endogenous acid production from dietary self-report instruments against recovery biomarker-derived measures |
Douglas Chang |
National Institute of Diabetes and Digestive and Kidney Diseases |
IDATA |
Mar 21, 2024 |
IDATA-71 |
Analysis of human energy and water requirements |
Dale Schoeller |
University of Wisconsin |
IDATA |
May 2, 2023 |
IDATA-64 |
Sleep Duration, Sleep Midpoint, Social Jetlag and Associations with Blood and Urine Metabolites in IDATA |
Joshua Freeman |
National Cancer Institute, Division of Cancer Epidemiology and Genetics |
IDATA |
Feb 24, 2023 |
IDATA-63 |
Feasibility of Short-term Individualized Dietary Recall Methodology Among U.S. Older Adults |
Alexandra Cowan |
Texas A&M University AgriLife Research, Institute for Advancing Health Through Agriculture |
IDATA |
Feb 10, 2023 |
IDATA-62 |
Metabolomic markers of physical activity in the IDATA Study |
Eleanor Watts |
National Cancer Institute |
IDATA |
Jan 13, 2023 |
IDATA-61 |
Sedentary Behavior Patterns: A Latent Class Trajectory Analysis of Within-Day SB Patterns |
Margaret Damare |
The University of North Carolina at Chapel Hill |
IDATA |
Dec 5, 2022 |
IDATA-60 |
Association between temporal dietary patterns and sedentary behaviors in middle-aged and older adults |
Zain Anderson |
University of North Carolina Chapel Hill |
IDATA |
Dec 5, 2022 |
IDATA-59 |
Diurnal pattern of physical activity and adherence to physical activity |
Tongyu Ma |
Franklin Pierce University |
IDATA |
Oct 3, 2022 |
IDATA-57 |
Mitigating measurement error and missing data impact on analysis of food frequency questionnaire data using machine learning methods |
Jennifer Frediani |
Emory University |
IDATA |
Aug 22, 2022 |
IDATA-56 |
A Systematic Review of the Validity of Dietary Assessment Methods for Measuring Energy Intake of Adults with Class III Obesity |
Valisa Hedrick |
Virginia Tech |
IDATA |
Jul 5, 2022 |
IDATA-55 |
Evaluation of measurement errors in total sugars and animal protein intakes assessed by self-reported dietary instruments using dietary biomarkers |
Natasha Tasevska |
Arizona State University |
IDATA |
Apr 1, 2022 |
2021-1004 |
Comparison of self-reported water intake against recovery biomarkers |
Douglas Chang |
National Institute of Diabetes and Digestive and Kidney Diseases |
IDATA |
Mar 25, 2022 |
IDATA-54 |
BRG IDATA Analyses |
Kevin Dodd |
National Cancer Institute, National Institutes of Health |
IDATA |
Mar 17, 2022 |
IDATA-53 |
Improving Measurement of Physical Activity and Sedentary Behavior |
Stephanie Eckman |
RTI International |
IDATA |
Nov 19, 2021 |
IDATA-50 |
Investigating the agreement of the composition and time spent in different physical activities derived from accelerometer data captured at different sensor locations |
Malcolm Granat |
University of Salford |
IDATA |
Oct 21, 2021 |
IDATA-49 |
Validating an Inference Engine for Data-driven Personalized Diet Goals |
Marissa Burgermaster |
University of Texas at Austin |
IDATA |
Jun 15, 2021 |
IDATA-46 |
Temporal Lifestyle Patterns Linked with Health Indicators |
Heather Eicher-Miller |
Purdue University |
IDATA |
May 27, 2021 |
IDATA-44 |