001     143760
005     20240229112607.0
024 7 _ |a 10.1161/CIRCULATIONAHA.118.038813
|2 doi
024 7 _ |a pmid:31006335
|2 pmid
024 7 _ |a 0009-7322
|2 ISSN
024 7 _ |a 0065-8499
|2 ISSN
024 7 _ |a 1524-4539
|2 ISSN
024 7 _ |a altmetric:59347925
|2 altmetric
037 _ _ |a DKFZ-2019-01329
041 _ _ |a eng
082 _ _ |a 610
100 1 _ |a Key, Timothy J
|b 0
245 _ _ |a Consumption of Meat, Fish, Dairy Products, Eggs and Risk of Ischemic Heart Disease: A Prospective Study of 7198 Incident Cases Among 409,885 Participants in the Pan-European EPIC Cohort.
260 _ _ |a [S.l.]
|c 2019
|b Ovid
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 1561713243_9537
|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
520 _ _ |a There is uncertainty about the relevance of animal foods to the etiology of ischemic heart disease (IHD). We examined meat, fish, dairy products and eggs and risk for IHD in the pan-European EPIC cohort.A prospective study of 409,885 men and women in nine European countries. Diet was assessed using validated questionnaires, calibrated using 24-hour recalls. Lipids and blood pressure were measured in a subsample. During 12.6 years mean follow up, 7198 participants had a myocardial infarction or died from IHD. The relationships of animal foods with risk were examined using Cox regression with adjustment for other animal foods and relevant covariates.The hazard ratio (HR) for IHD was 1.19 (95% CI 1.06-1.33) for a 100 g/d increment in intake of red and processed meat, and this remained significant after excluding the first 4 years of follow-up (HR 1.25 [1.09-1.42]). Risk was inversely associated with intakes of yogurt (HR 0.93 [0.89-0.98] per 100 g/d increment), cheese (HR 0.92 [0.86-0.98] per 30 g/d increment) and eggs (HR 0.93 [0.88-0.99] per 20 g/d increment); the associations with yogurt and eggs were attenuated and non-significant after excluding the first 4 years of follow-up. Risk was not significantly associated with intakes of poultry, fish or milk. In analyses modelling dietary substitutions, replacement of 100 kcal/d from red and processed meat with 100 kcal/d from fatty fish, yogurt, cheese or eggs was associated with approximately 20% lower risk of IHD. Consumption of red and processed meat was positively associated with serum non-HDL cholesterol concentration and systolic blood pressure, and consumption of cheese was inversely associated with serum non-HDL cholesterol.Risk for IHD was positively associated with consumption of red and processed meat, and inversely associated with consumption of yogurt, cheese and eggs, although the associations with yogurt and eggs may be influenced by reverse causation bias. It is not clear whether the associations with red and processed meat and cheese reflect causality, but they were consistent with the associations of these foods with plasma non-HDL cholesterol, and for red and processed meat with systolic blood pressure, which could mediate such effects.
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 Appleby, Paul N
|b 1
700 1 _ |a Bradbury, Kathryn E
|b 2
700 1 _ |a Sweeting, Michael
|b 3
700 1 _ |a Wood, Angela
|b 4
700 1 _ |a Johansson, Ingegerd
|b 5
700 1 _ |a Kühn, Tilman
|0 P:(DE-He78)0907a10ba1dc8f53f04907f54f6fdcfe
|b 6
|u dkfz
700 1 _ |a Steur, Marinka
|b 7
700 1 _ |a Weiderpass, Elisabete
|b 8
700 1 _ |a Wennberg, Maria
|b 9
700 1 _ |a Würtz, Anne Mette Lund
|b 10
700 1 _ |a Agudo, Antonio
|b 11
700 1 _ |a Andersson, Jonas
|b 12
700 1 _ |a Arriola, Larraitz
|b 13
700 1 _ |a Boeing, Heiner
|b 14
700 1 _ |a Boer, Jolanda M A
|b 15
700 1 _ |a Bonnet, Fabrice
|b 16
700 1 _ |a Boutron-Ruault, Marie-Christine
|b 17
700 1 _ |a Cross, Amanda J
|b 18
700 1 _ |a Ericson, Ulrika
|b 19
700 1 _ |a Fagherazzi, Guy
|b 20
700 1 _ |a Ferrari, Pietro
|b 21
700 1 _ |a Gunter, Marc
|b 22
700 1 _ |a Huerta, José María
|b 23
700 1 _ |a Katzke, Verena
|0 P:(DE-He78)fb68a9386399d72d84f7f34cfc6048b4
|b 24
|u dkfz
700 1 _ |a Khaw, Kay-Tee
|b 25
700 1 _ |a Krogh, Vittorio
|b 26
700 1 _ |a La Vecchia, Carlo
|b 27
700 1 _ |a Matullo, Giuseppe
|b 28
700 1 _ |a Moreno-Iribas, Conchi
|b 29
700 1 _ |a Naska, Androniki
|b 30
700 1 _ |a Nilsson, Lena Maria
|b 31
700 1 _ |a Olsen, Anja
|b 32
700 1 _ |a Overvad, Kim
|b 33
700 1 _ |a Palli, Domenico
|b 34
700 1 _ |a Panico, Salvatore
|b 35
700 1 _ |a Molina-Portillo, Elena
|b 36
700 1 _ |a Quirós, J Ramón
|b 37
700 1 _ |a Skeie, Guri
|b 38
700 1 _ |a Sluijs, Ivonne
|b 39
700 1 _ |a Sonestedt, Emily
|b 40
700 1 _ |a Stepien, Magdalena
|b 41
700 1 _ |a Tjønneland, Anne
|b 42
700 1 _ |a Trichopoulou, Antonia
|b 43
700 1 _ |a Tumino, Rosario
|b 44
700 1 _ |a Tzoulaki, Ioanna
|b 45
700 1 _ |a van der Schouw, Yvonne T
|b 46
700 1 _ |a Verschuren, W M Monique
|b 47
700 1 _ |a Di Angelantonio, Emanuele
|b 48
700 1 _ |a Langenberg, Claudia
|b 49
700 1 _ |a Forouhi, Nita
|b 50
700 1 _ |a Wareham, Nick
|b 51
700 1 _ |a Butterworth, Adam
|b 52
700 1 _ |a Riboli, Elio
|b 53
700 1 _ |a Danesh, John
|b 54
773 _ _ |a 10.1161/CIRCULATIONAHA.118.038813
|g p. CIRCULATIONAHA.118.038813
|0 PERI:(DE-600)1466401-x
|n 25
|p 2835-2845
|t Circulation
|v 139
|y 2019
|x 1524-4539
909 C O |o oai:inrepo02.dkfz.de:143760
|p VDB
910 1 _ |a Deutsches Krebsforschungszentrum
|0 I:(DE-588b)2036810-0
|k DKFZ
|b 6
|6 P:(DE-He78)0907a10ba1dc8f53f04907f54f6fdcfe
910 1 _ |a Deutsches Krebsforschungszentrum
|0 I:(DE-588b)2036810-0
|k DKFZ
|b 24
|6 P:(DE-He78)fb68a9386399d72d84f7f34cfc6048b4
913 1 _ |a DE-HGF
|l Krebsforschung
|1 G:(DE-HGF)POF3-310
|0 G:(DE-HGF)POF3-313
|2 G:(DE-HGF)POF3-300
|v Cancer risk factors and prevention
|x 0
|4 G:(DE-HGF)POF
|3 G:(DE-HGF)POF3
|b Gesundheit
914 1 _ |y 2019
915 _ _ |a Allianz-Lizenz
|0 StatID:(DE-HGF)0410
|2 StatID
915 _ _ |a Nationallizenz
|0 StatID:(DE-HGF)0420
|2 StatID
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0200
|2 StatID
|b SCOPUS
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 CIRCULATION : 2017
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 >= 15
|0 StatID:(DE-HGF)9915
|2 StatID
|b CIRCULATION : 2017
920 1 _ |0 I:(DE-He78)C020-20160331
|k C020
|l Epidemiologie von Krebserkrankungen
|x 0
980 _ _ |a journal
980 _ _ |a VDB
980 _ _ |a I:(DE-He78)C020-20160331
980 _ _ |a UNRESTRICTED


LibraryCollectionCLSMajorCLSMinorLanguageAuthor
Marc 21