Internet-Based and Self-Reports in Assessing Diet and Physical Activity Within AARP

NCT03268577 | Completed

• 3 other identifiers: NCI-2017-0118411CN155DCP-003
• Study Type: observational
• Target: 1,130
• Locations: 1 country
• Sites: 1

Brief Summary

This research trial studies how well internet-based and self-report instruments measure food intake and physical activity levels and their relationship with disease within American Association of Retired Persons (AARP) members. Comparing new internet-based questionnaires developed by the National Cancer Institute that report all the foods consumed and activities performed in an entire day to standardized physical measurements may help to determine if the information collected is accurate.

Conditions

Healthy Subject

Outcome Measures

Primary Outcomes (8)

• Self-reported energy intake from automated self-administered 24-hour dietary recall (ASA24), Diet History Questionnaire (DHQ)-II, and 4-day food record

  Will be evaluated against energy intake measured by doubly labeled water (DLW). Dietary intake of protein, potassium, and other nutrients will be compared to urinary nitrogen (UN), urinary potassium, and other nutrients measured in urine and blood.

  Up to 12 months

• Measurement error structure of self-reported active and sedentary behaviors (e.g. activity completed over time in 24-hours [ACT24], questionnaires)

  Will be examined using energy expenditure measured by DLW, physical activity monitor data, and hear rate monitor data. Data will be also used to evaluate alternative statistical methods for combining different types of self-report data on diet and physical activity-related behaviors as well as self-report plus objectively measured data.

  Up to 12 months

• 24-hour urine samples

  Will be analyzed for UN, potassium, para-amino benzoic acid (PABA), and other nutrients that are potential objective markers of intakes. First morning void urine also will be evaluated for its potential to be used as a source of biomarkers replacing 24-hr urine. Urine will be analyzed to characterize metabolic profiles of individuals.

  Up to 12 months

• Fasting blood sample analyses

  Will be processed to extract plasma and red and white blood cells, and analyzed in the future for vitamin C, folate, vitamin E, vitamin A, carotenoids, lipids, fatty acids and other nutrients.

  Up to 12 months

• Saliva samples

  Will be analyzed for oral microbiomes and to characterize metabolic profiles of individuals.

  Up to 12 months

• Measurement error structure of self-reported dietary assessment instruments

  Evaluated using latent-variable (measurement error) models. The models allow self-reported dietary intake to have intake-related and person-specific biases, but assume that reference biomarkers (doubly-labeled water, urinary nitrogen, urinary potassium) provide unbiased estimates of true usual intake at the individual level. Such models allow one to estimate the joint distribution of true and reported intake, and to estimate parameters of interest such as the correlation of true and reported intake and the "attenuation factor", or slope in the regression of true intake on reported intake.

  Up to 12 months

• Measurement error in self-reported total physical activity (measured in energy expenditure)

  Evaluated using latent-variable (measurement error) models. The models allow total energy expenditure derived from a physical activity monitor to have intake-related and person-specific biases, but assume that reference biomarkers (doubly-labeled water, urinary nitrogen, urinary potassium) provide unbiased estimates of true usual intake at the individual level. Such models to help develop better algorithms for estimating total energy expenditure from the measurements of physical activity monitors. For other physical activity measures of interest, such as minutes of vigorous activity or minutes of sedentary time per day, will use the physical activity monitors to derive approximately unbiased estimates that can be used as reference instruments.

  Up to 12 months

• Reduction in measurement error

  Will use multivariate measurement error models to estimate the joint distribution of true and reported values (nutrient intake, total energy, physical activity, body size). Then calculate residual reported intake (given reported total energy, physical activity and body size) and residual true intake (given true total energy, physical activity and body size), and assess the measurement error properties of reported residual intake as a measure of true residual intake. Specifically, will calculate the correlation of true and reported residual intake and the attenuation factor for residual reported intake and compare them to the same measures calculated for the simpler model that adjusts only for energy.

  Up to 12 months

Study Arms (1)

Prevention (diet and activity tracking)

Patients complete the ASA24 about foods, cooking methods, and other aspects of diet every 2 months for up to 6 times, and complete ACT24 about activities and time reporting every 2 months for up to 6 times. Patients also complete DHQ-II questionnaires at the beginning and end of the study about the frequency and portion sizes of foods consumed over the past 12 months, provide a 7-day food checklist twice with the DHQ-II, and provide a 4-day food record twice, once every 6 months. Physical activity monitors are worn to measure movement at different intensity levels and sitting or standing periods, twice during the study with 6 months between each time they are worn.

Other: Internet-Based Intervention; Device: Monitoring Device; Other: Questionnaire Administration

Interventions

Internet-Based Intervention OTHER

Complete ASA24

Prevention (diet and activity tracking)

Monitoring Device DEVICE

Wear accelerometer and inclinometer physical activity monitors

Also known as: Monitor

Prevention (diet and activity tracking)

Questionnaire Administration OTHER

Ancillary studies

Prevention (diet and activity tracking)

Eligibility Criteria

• Age: 50 Years - 74 Years
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Members within the existing NIH-AARP Diet and Health Study members (aged 50-71 in 1995-96) and younger AARP members born after 1945 ('baby boomers') and living in the Pittsburgh area in Pennsylvania

You may not qualify if:

• Non-English speaking or reading
• Weight loss diet (liquid or medications)
• Diabetes
• Body mass index \< 18.5 or \>= 40 (kg/m\^2)
• History of renal failure, congestive heart failure, or other conditions involving disturbances in fluid balance
• Limited mobility
• Use of supplemental oxygen
• Allergy to para-amino benzoic acid (PABA)
• No access to high-speed internet
• No more than one AARP member in the household can participate in the study

Sponsors & Collaborators

• National Cancer Institute (NCI): lead

Study Sites (1)

NCI Division of Cancer Control and Population Sciences

Rockville, Maryland, 20850, United States

Location

Related Publications (5)

• Chang DC, Dodd KW, Abramowitz MK, Barrett B, Stinson EJ. Validation of Net Endogenous Acid Production from the Automated Self-Administered 24-h Recall, 4-d Food Records, and a Food Frequency Questionnaire Using Urine Markers. J Nutr. 2025 Jun 30:S0022-3166(25)00402-X. doi: 10.1016/j.tjnut.2025.06.017. Online ahead of print.

  PMID: 40602721 DERIVED

• Abar L, Steele EM, Lee SK, Kahle L, Moore SC, Watts E, O'Connell CP, Matthews CE, Herrick KA, Hall KD, O'Connor LE, Freedman ND, Sinha R, Hong HG, Loftfield E. Identification and validation of poly-metabolite scores for diets high in ultra-processed food: An observational study and post-hoc randomized controlled crossover-feeding trial. PLoS Med. 2025 May 20;22(5):e1004560. doi: 10.1371/journal.pmed.1004560. eCollection 2025 May.

  PMID: 40392756 DERIVED

• Chang DC, Stinson EJ, Dodd KW, Bowles HR, Herrick KA, Schoeller DA, Barrett B, Votruba SB, Krakoff J, Kavouras SA. Validation of Total Water Intake from the Automated Self-Administered 24-h Recall, 4-d Food Records, and a Food Frequency Questionnaire Using Doubly Labeled Water. J Nutr. 2023 Oct;153(10):3049-3057. doi: 10.1016/j.tjnut.2023.08.027. Epub 2023 Sep 3.

  PMID: 37660952 DERIVED

• Shams-White MM, Korycinski RW, Dodd KW, Barrett B, Jacobs S, Subar AF, Park Y, Bowles HR. Examining the association between meal context and diet quality: an observational study of meal context in older adults. Int J Behav Nutr Phys Act. 2021 May 20;18(1):67. doi: 10.1186/s12966-021-01122-x.

  PMID: 34016140 DERIVED

• Subar AF, Potischman N, Dodd KW, Thompson FE, Baer DJ, Schoeller DA, Midthune D, Kipnis V, Kirkpatrick SI, Mittl B, Zimmerman TP, Douglass D, Bowles HR, Park Y. Performance and Feasibility of Recalls Completed Using the Automated Self-Administered 24-Hour Dietary Assessment Tool in Relation to Other Self-Report Tools and Biomarkers in the Interactive Diet and Activity Tracking in AARP (IDATA) Study. J Acad Nutr Diet. 2020 Nov;120(11):1805-1820. doi: 10.1016/j.jand.2020.06.015. Epub 2020 Aug 17.

  PMID: 32819883 DERIVED

Biospecimen

Retention: SAMPLES WITH DNA

saliva, urine, blood

MeSH Terms

Interventions

Monitoring, Physiologic

Intervention Hierarchy (Ancestors)

Diagnostic Techniques and Procedures; Diagnosis

Study Officials

• heather bowles

  NCI Division of Cancer Control and Population Sciences

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: NIH
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: August 30, 2017
• First Posted: August 31, 2017
• Study Start: January 1, 2012
• Primary Completion: December 31, 2013
• Study Completion: December 31, 2013
• Last Updated: June 4, 2020

Record last verified: 2020-06

Locations

US (1)