| Dietary biomarker development in the Interactive Diet and Activity Tracking in AARP Study |
Erikka Loftfield |
National Cancer Institute |
IDATA |
Dec 11, 2020 |
2020-1014 |
| Temporal dietary patterns and metabolic markers |
Yikyung Park |
Washington University in St. Louis |
IDATA |
Sep 11, 2020 |
2019-0001 |
| Reliability of 24-Hour Dietary Recall for Measuring Meal Timing |
Mary Playdon |
University of Utah |
IDATA |
Sep 11, 2020 |
IDATA-40 |
| Errors and uncertainty in the estimation of dietary mis-reporting in studies using doubly-labelled water to estimate energy intake |
Mark Hopkins |
University of Leeds |
IDATA |
Aug 10, 2020 |
IDATA-38 |
| Studying the association between diurnal rhythms of eating-fasting and rest-activity behaviors and oral microbiome. |
Qian Xiao |
The University of Texas Health Science Center at Houston |
IDATA |
Jul 17, 2020 |
IDATA-37 |
| The development of novel outcomes from free-living physical behaviour and their relationship with determinants of health |
Craig Speirs |
University of Strathclyde |
IDATA |
Jul 17, 2020 |
IDATA-36 |
| ActiGraph data for physical activity, gait and balance analysis |
Elias Abou Zeid |
Sanofi |
IDATA |
Apr 27, 2020 |
IDATA-35 |
| Relationship Among Energy Balance, Health Outcome, and 24-hour Time-Use Lifestyle Behaviors |
Yaozong He |
University of Illinois at Urbana-Champaign |
IDATA |
Mar 2, 2020 |
IDATA-34 |
| Integration and Analysis of Wearable Sensor Data for Biomarker Discovery |
Thomas Taylor |
INFOTECH Soft, Inc. |
IDATA |
Jan 6, 2020 |
IDATA-33 |
| Bias-correction of relative risks by robustly incorporating validation studies that include multiple methods of physical activity assessment and related biomarkers |
Xin Zhou |
Yale University |
IDATA |
Oct 15, 2019 |
IDATA-32 |
| Measurement error methods for wearable device data, treating daily measurements as imprecise draws from long-term average |
Dane Van Domelen |
Johns Hopkins Bloomberg School of Public Health |
IDATA |
Apr 8, 2019 |
IDATA-30 |
| Establishing a Physical Activity Regularity Index |
Seth Creasy |
University of Colorado Denver |
IDATA |
Jan 11, 2019 |
IDATA-29 |
| Temporal variation in the oral microbiota in the Interactive Diet and Activity Tracking in AARP Study |
Christian Abnet |
National Cancer Institute |
IDATA |
Dec 18, 2018 |
2018-0020 |
| Establishing Equivalence of Commonly Used Physical Activity Measures Using Testing Equating |
Zezhao Chen |
University of Illinois at Urbana Champaign |
IDATA |
Nov 13, 2018 |
IDATA-28 |
| Comparative analysis of scoring methods for the Healthy Eating Index-2015 across three dietary assessment instruments in IDATA |
Edwina Wambogo |
National Institutes of Health |
IDATA |
Sep 10, 2018 |
IDATA-26 |
| Use of previous-day recalls of physical activity and sedentary behavior in epidemiologic studies: results from four instruments |
Charles Matthews |
NCI / DCEG / Metabolic Epidemiology Branch |
IDATA |
Aug 21, 2018 |
IDATA-25 |
| Harmonisation of physical activity measures |
Soren Brage |
MRC Epidemiology Unit, University of Cambridge |
IDATA |
Aug 21, 2018 |
IDATA-24 |
| Functional Relationships between Body Composition, Energy Expenditure and Daily Food Intake |
Mark Hopkins |
University of Leeds |
IDATA |
Aug 6, 2018 |
IDATA-23 |
| Characterizing Free-Living Stepping Behavior |
Kate Lyden |
KAL Research|Consulting, PAL Technologies |
IDATA |
Apr 16, 2018 |
IDATA-21 |
| Revising free text inputs in physical activity self-report methods: Lessons from the ACT24 |
Robert Korycinski |
National Cancer Institute |
IDATA |
Jan 19, 2018 |
IDATA-20 |
