Evidence map›Paper›PMID 26354543›Full record

SynthesisThe American journal of clinical nutrition2015

Consumption of meat is associated with higher fasting glucose and insulin concentrations regardless of glucose and insulin genetic risk scores: a meta-analysis of 50,345 Caucasians.

Amanda M Fretts, Jack L Follis, Jennifer A Nettleton, Rozenn N Lemaitre, Julius S Ngwa, Mary K Wojczynski, Ioanna Panagiota Kalafati, Tibor V Varga, Alexis C Frazier-Wood, Denise K Houston and 52 more

5 registry-linked trialsOpen access · greenAbstract readMeta-Analysis
In one paragraph

Synthesis in The American journal of clinical nutrition, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 5 registered trials, which are not on this map. Cited by 43 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
43citing papers in PubMed, 4 pooled it
8.3field-weighted citation impact, top 2% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT00005121 completednot on this map

Framingham Heart Study

TypeobservationalSponsorNational Heart, Lung, and Blood Institute (NHLBI)Ran1948 to 2008ConditionsCardiovascular Diseases, Heart Diseases, Coronary Disease, Cerebrovascular Accident
NCT00005136 completednot on this map

Family Heart Study (FHS)

TypeobservationalSponsorUniversity of MinnesotaRan1992 to 2005ConditionsCardiovascular Diseases, Atherosclerosis, Coronary Disease, Heart Diseases
NCT00005487 active not recruitingnot on this map

Multi-Ethnic Study of Atherosclerosis (MESA)

TypeobservationalSponsorNational Heart, Lung, and Blood Institute (NHLBI)Ran1999 to 2030Enrolled6,418ConditionsAtherosclerosis, Cardiovascular Diseases, Heart Diseases, Coronary Artery Disease
NCT00083369 completednot on this map

Genetic and Environmental Determinants of Triglycerides (GOLDN)

TypeobservationalSponsorUniversity of Alabama at BirminghamRan2002 to 2009Enrolled1,327ConditionsAtherosclerosis, Cardiovascular Diseases, Heart Diseases
NCT00149435 completednot on this map

Cardiovascular Health Study (CHS) Events Follow-up Study

TypeobservationalSponsorUniversity of WashingtonRan2005 to 2009Enrolled5,888ConditionsCardiovascular Diseases, Coronary Disease, Cerebrovascular Accident, Diabetes Mellitus
3 · Its place in the literature

Who cites it

43 citing papers in PubMed, 4 syntheses or guidelines pooled it, 92 citations in OpenAlex.

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  19. TT Genotype ofNutrients · 2023
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

62 authors at 20 institutions in 11 countries.

Amanda M FrettsDepartments of Epidemiology, Cardiovascular Health Research Unit, University of Washington, Seattle, WA; amfretts@uw.edu.
Jack L FollisDepartment of Mathematics, Computer Science, and Cooperative Engineering, University of St. Thomas, Houston, TX;
Jennifer A NettletonDivision of Epidemiology, Human Genetics, and Environmental Sciences, University of Texas Health Sciences Center, Houston, TX;
Rozenn N LemaitreMedicine, Cardiovascular Health Research Unit, University of Washington, Seattle, WA;
Julius S NgwaDepartment of Biostatistics, Boston University School of Public Health, Boston, MA;
Mary K WojczynskiDepartment of Genetics, Division of Statistical Genomics, School of Medicine, Washington University, St. Louis, MO;
Ioanna Panagiota KalafatiDepartment of Nutrition and Dietetics, Harokopio University of Athens, Athens, Greece;
Tibor V VargaDepartment of Clinical Sciences Genetic and Molecular Epidemiology Unit and.
Alexis C Frazier-WoodUSDA/Agricultural Research Service Children's Nutrition Research Center, Department of Pediatrics, Baylor College of Medicine, Houston, TX;
Denise K HoustonDepartment of Internal Medicine and.
Jari LahtiInstitute of Behavioral Sciences.
Ulrika EricsonDepartment of Clinical Sciences, Lund University, Malmö, Sweden;
Edith H van den HoovenDepartment of Epidemiology and.
Vera MikkiläDepartment of Food and Environmental Sciences, and Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland;
Jessica C Kiefte-de JongDepartment of Epidemiology and.
Dariush MozaffarianFriedman School of Nutrition Science & Policy, Tufts University, Boston, MA;
Kenneth RiceBiostatistics, and Cardiovascular Health Research Unit, University of Washington, Seattle, WA;
Frida RenströmDepartment of Clinical Sciences Genetic and Molecular Epidemiology Unit and Department of Biobank Research.
Kari E NorthDepartment of Epidemiology, Carolina Center for Genome Sciences, University of North Carolina, Chapel Hill, NC;
Nicola M McKeownNutritional Epidemiology Program, Jean Mayer-USDA Human Nutrition Research Center on Aging, and.
Mary F FeitosaDepartment of Genetics, Division of Statistical Genomics, School of Medicine, Washington University, St. Louis, MO;
Stavroula KanoniWilliam Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom;
Caren E SmithNutrition and Genomics Laboratory, Tufts University, Boston, MA;
Melissa E GarciaLaboratory of Epidemiology and Population Sciences and.
Anna-Maija TiainenDepartment of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Finland;
Emily SonestedtDepartment of Clinical Sciences, Lund University, Malmö, Sweden;
Ani ManichaikulCenter for Public Health Genomics, Department of Public Health Sciences, Division of Biostatistics and Epidemiology, University of Virginia, Charlottesville, VA;
Frank J A van RooijDepartment of Epidemiology and Netherlands Genomics Initiative, Leiden, Netherlands;
Maria DimitriouDepartment of Nutrition and Dietetics, Harokopio University of Athens, Athens, Greece;
Olli RaitakariResearch Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland; Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland;
James S PankowDivision of Epidemiology and Community Health, University of Minnesota, Minneapolis, MN;
Luc DjousséDepartment of Medicine Brigham and Women's Hospital, Harvard Medical School, Boston MA and.
Michael A ProvinceDepartment of Genetics, Division of Statistical Genomics, School of Medicine, Washington University, St. Louis, MO;
Frank B HuDepartment of Epidemiology and Department of Nutrition, Harvard School of Public Health, Boston, MA;
Chao-Qiang LaiJean Mayer-USDA Human Nutrition Research Center on Aging, and Nutrition and Genomics Laboratory, Tufts University, Boston, MA;
Margaux F KellerLaboratory of Neurogenetics, National Institute of Aging, Bethesda, MD; Department of Clinical Physiology.
Mia-Maria PeräläDepartment of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Finland;
Jerome I RotterInstitute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA;
Albert HofmanDepartment of Epidemiology and.
Misa GraffDepartment of Epidemiology.
Mika KähönenSchool of Medicine, and Tampere University Hospital, University of Tampere, Tampere, Finland;
Kenneth MukamalDivision of General Medicine and Primary Care, Beth Israel Deaconess Medical Center, Boston, MA;
Ingegerd JohanssonDepartment of Odontology, and.
Jose M OrdovasJean Mayer-USDA Human Nutrition Research Center on Aging, and Nutrition and Genomics Laboratory, Tufts University, Boston, MA; Department of Epidemiology and Population Genetics, Cardiovascular Research Center, Madrid, Spain; IMDEA Food Institute, Madrid, Spain;
Yongmei LiuDepartment of Epidemiology and Prevention, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC;
Satu MännistöDepartment of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Finland;
André G UitterlindenDepartment of Epidemiology and Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, Netherlands;
Panos DeloukasWilliam Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom; Princess Al-Jawhara Al-Brahim Centre of Excellence in Research of Hereditary Disorders, King Abdulaziz University, Jeddah, Saudi Arabia;
Ilkka SeppäläDepartment of Clinical Chemistry, Fimlab Laboratories, School of Medicine, and.
Bruce M PsatyDepartments of Epidemiology, Medicine, Health Services and Cardiovascular Health Research Unit, University of Washington, Seattle, WA; Group Health Research Institute, Group Health Cooperative, Seattle, WA.
L Adrienne CupplesDepartment of Biostatistics, Boston University School of Public Health, Boston, MA; Framingham Heart Study, Framingham, MA;
Ingrid B BoreckiDepartment of Genetics, Division of Statistical Genomics, School of Medicine, Washington University, St. Louis, MO;
Paul W FranksDepartment of Clinical Sciences Genetic and Molecular Epidemiology Unit and Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden; Department of Nutrition, Harvard School of Public Health, Boston, MA;
Donna K ArnettDepartment of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL;
Mike A NallsLaboratory of Neurogenetics, National Institute of Aging, Bethesda, MD;
Johan G ErikssonDepartment of General Practice and Primary Health Care, University of Helsinki, Helsinki, Finland; Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Finland; General Practice Unit, Helsinki University Central Hospital, Helsinki, Finland; Folkhälsan Research Center, Helsinki, Finland;
Marju Orho-MelanderDepartment of Clinical Sciences, Lund University, Malmö, Sweden;
Oscar H FrancoDepartment of Epidemiology and.
Terho LehtimäkiDepartment of Clinical Chemistry, Fimlab Laboratories, School of Medicine, and.
George V DedoussisDepartment of Nutrition and Dietetics, Harokopio University of Athens, Athens, Greece;
James B MeigsClinical Epidemiology Unit and Diabetes Research Unit, General Medicine Division, Massachusetts General Hospital, Boston, MA; and.
David S SiscovickDepartments of Epidemiology, Medicine, Cardiovascular Health Research Unit, University of Washington, Seattle, WA; New York Academy of Medicine, New York, NY.
Tufts University · USErasmus University Rotterdam · NLLund University · SEWashington University in St. Louis · USFinnish Institute for Health and Welfare · FIHarokopio University of Athens · GRNational Institutes of Health · USTampere University · FIUniversity of Washington · USBoston University · USHarvard University Press · USQueen Mary University of London · GBUniversity of Helsinki · FIUniversity of North Carolina at Chapel Hill · USUniversity of Turku · FIWake Forest University · USAgricultural Research Service · USBeth Israel Deaconess Medical Center · USBrigham and Women's Hospital · USCentro de Ingeniería Genética y Biotecnología · CU

Funding

Transform Dissemination and Implementation Science in CTSA ProgramsUL1TR002319 · NCATS · UNIVERSITY OF WASHINGTON · PI John K. Amory · 2017 to 2026
$100.0M
UCLA Clinical and Translational Science InstituteUL1TR000124 · NCATS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI DUBINETT, STEVEN M. · 2012 to 2015
$57.0M
Transgenic & Knock-out MouseP30DK063491 · NIDDK · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI Andrea L Hevener · 2003 to 2026
$40.4M
University of Alabama at Birmingham's Diabetes Research CenterP30DK079626 · NIDDK · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI Kirk Michael Habegger · 2013 to 2026
$19.5M
Institute of Translational Health SciencesKL2TR000421 · NCATS · UNIVERSITY OF WASHINGTON · PI DISIS, MARY L. · 2012 to 2016
$12.6M
Genetic and Environmental Determinants of TriglyceridesU01HL072524 · NHLBI · UNIVERSITY OF MINNESOTA TWIN CITIES · PI ARNETT, DONNA K · 2002 to 2008
$11.9M
CHARGE Consortium: Omics Discovery for CVD and Aging PhenotypesR01HL105756 · NHLBI · UNIVERSITY OF WASHINGTON · PI Bruce M Psaty, NICHOLAS L SMITH · 2011 to 2026
$9.5M
Rare variants and NHLBI traits in deeply phenotyped cohortsR01HL120393 · NHLBI · UNIVERSITY OF WASHINGTON · PI PSATY, BRUCE M, RICE, KENNETH M. · 2014 to 2016
$8.9M
Genomewide Association Study of Lipid Response to Fenofibrate and Dietary FatR01HL091357 · NHLBI · UNIVERSITY OF KENTUCKY · PI ARNETT, DONNA K · 2008 to 2018
$5.8M
Common Genetic Variation and Quantitative Diabetes TraitsR01DK078616 · NIDDK · MASSACHUSETTS GENERAL HOSPITAL · PI MEIGS, JAMES B · 2008 to 2014
$5.0M
CVD Epidemiology Training ProgramT32HL007902 · NHLBI · UNIVERSITY OF WASHINGTON · PI PSATY, BRUCE M · 1998 to 2012
$3.6M
Rare Sequence Variation and Diabetes Quantitative TraitsU01DK078616 · NIDDK · MASSACHUSETTS GENERAL HOSPITAL · PI MEIGS, JAMES B · 2015 to 2019
$3.6M
NCATS NIH HHS 5KL2TR000421-08NCATS NIH HHS KL2 TR000421NCATS NIH HHS UL1 TR000124NCATS NIH HHS UL1 TR002319NHLBI NIH HHS K08 HL112845NHLBI NIH HHS R01 HL091357NHLBI NIH HHS R01 HL105756NHLBI NIH HHS R01HL105756NHLBI NIH HHS R01 HL117078NHLBI NIH HHS R01 HL120393NHLBI NIH HHS T32HL007902NHLBI NIH HHS U01 HL072524NIDDK NIH HHS K24 DK080140NIDDK NIH HHS P30 DK063491NIDDK NIH HHS P30 DK079626NIDDK NIH HHS R01 DK078616NIDDK NIH HHS U01 DK078616
6 · The paper itself

Abstract

backgroundRecent studies suggest that meat intake is associated with diabetes-related phenotypes. However, whether the associations of meat intake and glucose and insulin homeostasis are modified by genes related to glucose and insulin is unknown.

objectiveWe investigated the associations of meat intake and the interaction of meat with genotype on fasting glucose and insulin concentrations in Caucasians free of diabetes mellitus.

designFourteen studies that are part of the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium participated in the analysis. Data were provided for up to 50,345 participants. Using linear regression within studies and a fixed-effects meta-analysis across studies, we examined 1) the associations of processed meat and unprocessed red meat intake with fasting glucose and insulin concentrations; and 2) the interactions of processed meat and unprocessed red meat with genetic risk score related to fasting glucose or insulin resistance on fasting glucose and insulin concentrations.

resultsProcessed meat was associated with higher fasting glucose, and unprocessed red meat was associated with both higher fasting glucose and fasting insulin concentrations after adjustment for potential confounders [not including body mass index (BMI)]. For every additional 50-g serving of processed meat per day, fasting glucose was 0.021 mmol/L (95% CI: 0.011, 0.030 mmol/L) higher. Every additional 100-g serving of unprocessed red meat per day was associated with a 0.037-mmol/L (95% CI: 0.023, 0.051-mmol/L) higher fasting glucose concentration and a 0.049-ln-pmol/L (95% CI: 0.035, 0.063-ln-pmol/L) higher fasting insulin concentration. After additional adjustment for BMI, observed associations were attenuated and no longer statistically significant. The association of processed meat and fasting insulin did not reach statistical significance after correction for multiple comparisons. Observed associations were not modified by genetic loci known to influence fasting glucose or insulin resistance.

conclusionThe association of higher fasting glucose and insulin concentrations with meat consumption was not modified by an index of glucose- and insulin-related single-nucleotide polymorphisms. Six of the participating studies are registered at clinicaltrials.gov as NCT0000513 (Atherosclerosis Risk in Communities), NCT00149435 (Cardiovascular Health Study), NCT00005136 (Family Heart Study), NCT00005121 (Framingham Heart Study), NCT00083369 (Genetics of Lipid Lowering Drugs and Diet Network), and NCT00005487 (Multi-Ethnic Study of Atherosclerosis).

Indexed as

Insulin ResistanceBlood GlucoseCohort StudiesGenetic Association StudiesGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansHyperglycemiaHyperinsulinismInsulinInsulin-Secreting CellsInsulin SecretionMeatMeat ProductsMiddle AgedPolymorphism, Single NucleotideBlood GlucoseInsulindietgene–diet interactionglucoseinsulinmeat intakemeta-analysis

Identifiers

PMID26354543
PMCPMC4625584
OpenAlexW1960884834

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.