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Food groups and risk of all-cause mortality_ a systematic review and meta-analysis of prospective studies12.pdf 970,18KB
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1000 Titel
  • Food groups and risk of all-cause mortality: a systematic review and meta-analysis of prospective studies
1000 Autor/in
  1. Schwingshackl, Lukas |
  2. Schwedhelm, Carolina |
  3. Hoffmann, Georg |
  4. Lampousi, Anna-Maria |
  5. Knüppel, Sven |
  6. Iqbal, Khalid |
  7. Bechthold, Angela |
  8. Schlesinger, Sabrina |
  9. Boeing, Heiner |
1000 Erscheinungsjahr 2017
1000 LeibnizOpen
1000 Art der Datei
1000 Publikationstyp
  1. Artikel |
1000 Online veröffentlicht
  • 2017-04-26
1000 Erschienen in
1000 Quellenangabe
  • 105(6):1462-1473
1000 FRL-Sammlung
1000 Copyrightjahr
  • 2017
1000 Lizenz
1000 Verlagsversion
  • https://doi.org/10.3945/ajcn.117.153148 |
  • https://www.ncbi.nlm.nih.gov/pubmed/28446499 |
1000 Ergänzendes Material
  • https://academic.oup.com/ajcn/article/105/6/1462/4569801 |
1000 Publikationsstatus
1000 Begutachtungsstatus
1000 Sprache der Publikation
1000 Abstract/Summary
  • BACKGROUND: Suboptimal diet is one of the most important factors in preventing early death and disability worldwide. OBJECTIVE: The aim of this meta-analysis was to synthesize the knowledge about the relation between intake of 12 major food groups, including whole grains, refined grains, vegetables, fruits, nuts, legumes, eggs, dairy, fish, red meat, processed meat, and sugar-sweetened beverages, with risk of all-cause mortality. DESIGN: We conducted a systematic search in PubMed, Embase, and Google Scholar for prospective studies investigating the association between these 12 food groups and risk of all-cause mortality. Summary RRs and 95% CIs were estimated with the use of a random effects model for high-intake compared with low-intake categories, as well as for linear and nonlinear relations. Moreover, the risk reduction potential of foods was calculated by multiplying the RR by optimal intake values (serving category with the strongest association) for risk-reducing foods or risk-increasing foods, respectively. RESULTS: With increasing intake (for each daily serving) of whole grains (RR: 0.92; 95% CI: 0.89, 0.95), vegetables (RR: 0.96; 95% CI: 0.95, 0.98), fruits (RR: 0.94; 95% CI: 0.92, 0.97), nuts (RR: 0.76; 95% CI: 0.69, 0.84), and fish (RR: 0.93; 95% CI: 0.88, 0.98), the risk of all-cause mortality decreased; higher intake of red meat (RR: 1.10; 95% CI: 1.04, 1.18) and processed meat (RR: 1.23; 95% CI: 1.12, 1.36) was associated with an increased risk of all-cause mortality in a linear dose-response meta-analysis. A clear indication of nonlinearity was seen for the relations between vegetables, fruits, nuts, and dairy and all-cause mortality. Optimal consumption of risk-decreasing foods results in a 56% reduction of all-cause mortality, whereas consumption of risk-increasing foods is associated with a 2-fold increased risk of all-cause mortality. CONCLUSION: Selecting specific optimal intakes of the investigated food groups can lead to a considerable change in the risk of premature death.
1000 Sacherschließung
lokal dose response
lokal food groups
lokal meta-analysis
lokal mortality
lokal diet
1000 Fachgruppe
  1. Ernährungswissenschaften |
1000 Fächerklassifikation (DDC)
1000 Liste der Beteiligten
  1. http://orcid.org/0000-0003-3407-7594|https://frl.publisso.de/adhoc/creator/U2Nod2VkaGVsbSwgQ2Fyb2xpbmE=|https://frl.publisso.de/adhoc/creator/SG9mZm1hbm4sIEdlb3Jn|https://frl.publisso.de/adhoc/creator/TGFtcG91c2ksIEFubmEtTWFyaWE=|https://frl.publisso.de/adhoc/creator/S27DvHBwZWwsIFN2ZW4=|https://frl.publisso.de/adhoc/creator/SXFiYWwsIEtoYWxpZA==|https://frl.publisso.de/adhoc/creator/QmVjaHRob2xkLCBBbmdlbGE=|http://orcid.org/0000-0003-4244-0832|http://orcid.org/0000-0002-3358-1775
1000 Label
1000 Förderer
  1. National Health Service Biomedical Research Centre |
1000 Fördernummer
  1. -
1000 Förderprogramm
  1. -
1000 Dateien
  1. Food groups and risk of all-cause mortality: a systematic review and meta-analysis of prospective studies
  2. Rightslink® by Copyright Clearance Center.pdf
1000 Förderung
  1. 1000 joinedFunding-child
    1000 Förderer National Health Service Biomedical Research Centre |
    1000 Förderprogramm -
    1000 Fördernummer -
1000 Objektart article
1000 Beschrieben durch
1000 @id frl:6407186.rdf
1000 Erstellt am 2018-03-19T12:43:15.926+0100
1000 Erstellt von 218
1000 beschreibt frl:6407186
1000 Bearbeitet von 218
1000 Zuletzt bearbeitet Thu Jan 30 18:50:32 CET 2020
1000 Objekt bearb. Tue Sep 04 10:04:09 CEST 2018
1000 Vgl. frl:6407186
1000 Oai Id
  1. oai:frl.publisso.de:frl:6407186 |
1000 Sichtbarkeit Metadaten public
1000 Sichtbarkeit Daten public
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