Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 1,401

The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.

Comparative Validation of the Block, Willett, and National Cancer Institute Food Frequency Questionnaires

Open access
Subar, Amy F., Thompson, Frances E., Kipnis, Victor, Midthune, Douglas, Hurwitz, Paul, McNutt, Suzanne, McIntosh, Anna, Rosenfeld, Simon·2001·American Journal of Epidemiology

Abstract

Researchers at the National Cancer Institute developed a new cognitively based food frequency questionnaire (FFQ), the Diet History Questionnaire (DHQ). The Eating at America's Table Study sought to validate and compare the DHQ with the Block and Willett FFQs. Of 1,640 men and women recruited to participate from a nationally representative sample in 1997, 1,301 completed four telephone 24-hour recalls, one in each season. Participants were randomized to receive either a DHQ and Block FFQ or a DHQ and Willett FFQ. With a standard measurement error model, correlations for energy between estimated truth and the DHQ, Block FFQ, and Willett FFQ, respectively, were 0.48, 0.45, and 0.18 for women and 0.49, 0.45, and 0.21 for men. For 26 nutrients, correlations and attenuation coefficients were somewhat higher for the DHQ versus the Block FFQ, and both were better than the Willett FFQ in models unadjusted for energy. Energy adjustment increased correlations and attenuation coefficients for the Willett FFQ dramatically and for the DHQ and Block FFQ instruments modestly. The DHQ performed best overall. These data show that the DHQ and the Block FFQ are better at estimating absolute intakes than is the Willett FFQ but that, after energy adjustment, all three are more comparable for purposes of assessing diet-disease risk.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1093/aje/154.12.1089

Cites

8 of 8 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Cited by

See all 1,401

Metadata

Authors
Subar, A. F., Thompson, F. E., Kipnis, V., Midthune, D., Hurwitz, P., McNutt, S., McIntosh, A., & Rosenfeld, S.
Venue
American Journal of Epidemiology
Published
2001-12-15
Volume
154
Issue
12
Pages
1089-1099
ISSN
  • 0002-9262 (ISSN-L)
  • 1476-6256
OpenAlex
W2087279974
Cited by
1,401
References
8
FWCI
21.77
Type
journal article
Language
en
Open access
hybrid

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.