001     143000
005     20240229112539.0
024 7 _ |a 10.1038/s41430-018-0383-8
|2 doi
024 7 _ |a pmid:30647440
|2 pmid
024 7 _ |a 0954-3007
|2 ISSN
024 7 _ |a 1476-5640
|2 ISSN
024 7 _ |a altmetric:54644050
|2 altmetric
037 _ _ |a DKFZ-2019-00625
041 _ _ |a eng
082 _ _ |a 630
100 1 _ |a Knüppel, Sven
|0 0000-0001-9006-9906
|b 0
245 _ _ |a Design and characterization of dietary assessment in the German National Cohort.
260 _ _ |a New York, NY
|c 2019
|b Nature Publ. Group
336 7 _ |a article
|2 DRIVER
336 7 _ |a Output Types/Journal article
|2 DataCite
336 7 _ |a Journal Article
|b journal
|m journal
|0 PUB:(DE-HGF)16
|s 1636548375_12226
|2 PUB:(DE-HGF)
336 7 _ |a ARTICLE
|2 BibTeX
336 7 _ |a JOURNAL_ARTICLE
|2 ORCID
336 7 _ |a Journal Article
|0 0
|2 EndNote
500 _ _ |a 73(11):1480-1491
520 _ _ |a The aim of the study was to describe a novel dietary assessment strategy based on two instruments complemented by information from an external population applied to estimate usual food intake in the large-scale multicenter German National Cohort (GNC). As proof of concept, we applied the assessment strategy to data from a pretest study (2012-2013) to assess the feasibility of the novel assessment strategy.First, the consumption probability for each individual was modeled using three 24 h food lists (24h-FLs) and frequencies from one food frequency questionnaire (FFQ). Second, daily consumed food amounts were estimated from the representative German National Nutrition Survey II (NVS II) taking the characteristics of the participants into account. Usual food intake was estimated using the product of consumption probability and amounts.We estimated usual intake of 41 food groups in 318 men and 377 women. The participation proportion was 100, 84.4, and 68.5% for the first, second, and third 24h-FL, respectively. We observed no associations between the probability of participating and lifestyle factors. The estimated distributions of usual food intakes were plausible and total energy was estimated to be 2707 kcal/day for men and 2103 kcal/day for women. The estimated consumption frequencies did not differ substantially between men and women with only few exceptions. The differences in energy intake between men and women were mostly due to differences in estimated daily amounts.The combination of repeated 24h-FLs, a FFQ, and consumption-day amounts from a reference population represents a user-friendly dietary assessment approach having generated plausible, but not yet validated, food intake values in the pretest study.
536 _ _ |a 313 - Cancer risk factors and prevention (POF3-313)
|0 G:(DE-HGF)POF3-313
|c POF3-313
|f POF III
|x 0
588 _ _ |a Dataset connected to CrossRef, PubMed,
700 1 _ |a Clemens, Matthias
|b 1
700 1 _ |a Conrad, Johanna
|b 2
700 1 _ |a Gastell, Sylvia
|b 3
700 1 _ |a Michels, Karin B
|b 4
700 1 _ |a Leitzmann, Michael
|b 5
700 1 _ |a Krist, Lilian
|b 6
700 1 _ |a Pischon, Tobias
|b 7
700 1 _ |a Krause, Gerard
|b 8
700 1 _ |a Ahrens, Wolfgang
|b 9
700 1 _ |a Ebert, Nina
|b 10
700 1 _ |a Jöckel, Karl-Heinz
|b 11
700 1 _ |a Kluttig, Alexander
|b 12
700 1 _ |a Obi, Nadia
|b 13
700 1 _ |a Kaaks, Rudolf
|0 P:(DE-He78)4b2dc91c9d1ac33a1c0e0777d0c1697a
|b 14
|u dkfz
700 1 _ |a Lieb, Wolfgang
|b 15
700 1 _ |a Schipf, Sabine
|b 16
700 1 _ |a Brenner, Hermann
|0 P:(DE-He78)90d5535ff896e70eed81f4a4f6f22ae2
|b 17
|u dkfz
700 1 _ |a Heuer, Thorsten
|b 18
700 1 _ |a Harttig, Ulrich
|b 19
700 1 _ |a Linseisen, Jakob
|b 20
700 1 _ |a Nöthlings, Ute
|b 21
700 1 _ |a Boeing, Heiner
|b 22
773 _ _ |a 10.1038/s41430-018-0383-8
|0 PERI:(DE-600)2004986-9
|n 11
|p 1480-1491
|t European journal of clinical nutrition
|v 73
|y 2019
|x 1476-5640
909 C O |p VDB
|o oai:inrepo02.dkfz.de:143000
910 1 _ |a Deutsches Krebsforschungszentrum
|0 I:(DE-588b)2036810-0
|k DKFZ
|b 14
|6 P:(DE-He78)4b2dc91c9d1ac33a1c0e0777d0c1697a
910 1 _ |a Deutsches Krebsforschungszentrum
|0 I:(DE-588b)2036810-0
|k DKFZ
|b 17
|6 P:(DE-He78)90d5535ff896e70eed81f4a4f6f22ae2
913 1 _ |a DE-HGF
|b Gesundheit
|l Krebsforschung
|1 G:(DE-HGF)POF3-310
|0 G:(DE-HGF)POF3-313
|3 G:(DE-HGF)POF3
|2 G:(DE-HGF)POF3-300
|4 G:(DE-HGF)POF
|v Cancer risk factors and prevention
|x 0
914 1 _ |y 2019
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0300
|2 StatID
|b Medline
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0310
|2 StatID
|b NCBI Molecular Biology Database
915 _ _ |a JCR
|0 StatID:(DE-HGF)0100
|2 StatID
|b EUR J CLIN NUTR : 2017
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0200
|2 StatID
|b SCOPUS
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0600
|2 StatID
|b Ebsco Academic Search
915 _ _ |a Peer Review
|0 StatID:(DE-HGF)0030
|2 StatID
|b ASC
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0199
|2 StatID
|b Clarivate Analytics Master Journal List
915 _ _ |a WoS
|0 StatID:(DE-HGF)0110
|2 StatID
|b Science Citation Index
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0150
|2 StatID
|b Web of Science Core Collection
915 _ _ |a WoS
|0 StatID:(DE-HGF)0111
|2 StatID
|b Science Citation Index Expanded
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1110
|2 StatID
|b Current Contents - Clinical Medicine
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1030
|2 StatID
|b Current Contents - Life Sciences
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1050
|2 StatID
|b BIOSIS Previews
915 _ _ |a IF < 5
|0 StatID:(DE-HGF)9900
|2 StatID
920 1 _ |0 I:(DE-He78)C020-20160331
|k C020
|l C020 Epidemiologie von Krebs
|x 0
920 1 _ |0 I:(DE-He78)C120-20160331
|k C120
|l Präventive Onkologie
|x 1
920 1 _ |0 I:(DE-He78)C070-20160331
|k C070
|l C070 Klinische Epidemiologie und Alternf.
|x 2
920 1 _ |0 I:(DE-He78)L101-20160331
|k L101
|l DKTK Heidelberg
|x 3
980 _ _ |a journal
980 _ _ |a VDB
980 _ _ |a I:(DE-He78)C020-20160331
980 _ _ |a I:(DE-He78)C120-20160331
980 _ _ |a I:(DE-He78)C070-20160331
980 _ _ |a I:(DE-He78)L101-20160331
980 _ _ |a UNRESTRICTED


LibraryCollectionCLSMajorCLSMinorLanguageAuthor
Marc 21