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

被引：66

作者：

Fretts, Amanda M. ^{[1
,5
]}

Follis, Jack L. ^{[8
]}

Nettleton, Jennifer A. ^{[7
]}

Lemaitre, Rozenn N. ^{[2
,5
]}

Ngwa, Julius S. ^{[9
]}

Wojczynski, Mary K. ^{[10
]}

Kalafati, Ioanna Panagiota ^{[11
]}

Varga, Tibor V. ^{[12
]}

Frazier-Wood, Alexis C. ^{[6
]}

Houston, Denise K. ^{[17
]}

Lahti, Jari ^{[19
]}

Ericson, Ulrika ^{[13
]}

van den Hooven, Edith H. ^{[22
]}

Mikkilae, Vera ^{[20
,24
]}

Kiefte-de Jong, Jessica C. ^{[22
]}

Mozaffarian, Dariush ^{[28
]}

Rice, Kenneth ^{[3
]}

Renstroem, Frida ^{[12
,14
]}

North, Kari E. ^{[29
,30
]}

McKeown, Nicola M. ^{[31
,32
]}

Feitosa, Mary F. ^{[10
]}

Kanoni, Stavroula ^{[34
,35
]}

Smith, Caren E. ^{[33
]}

Garcia, Melissa E. ^{[36
]}

Tiainen, Anna-Maija ^{[38
]}

Sonestedt, Emily ^{[13
]}

Manichaikul, Ani ^{[39
]}

van Rooij, Frank J. A. ^{[22
,40
]}

Dimitriou, Maria ^{[11
]}

Raitakari, Olli ^{[24
,41
]}

Pankow, James S. ^{[42
]}

Djousse, Luc ^{[27
]}

Province, Michael A. ^{[10
]}

Hu, Frank B. ^{[25
,26
]}

Lai, Chao-Qiang ^{[32
,33
]}

Keller, Margaux F. ^{[37
,44
]}

Peraelae, Mia-Maria ^{[38
]}

Rotter, Jerome I. ^{[43
]}

Hofman, Albert ^{[22
]}

Graff, Misa ^{[29
]}

Kaehoenen, Mika ^{[47
,48
]}

Mukamal, Kenneth ^{[49
]}

Johansson, Ingegerd ^{[15
]}

Ordovas, Jose M. ^{[32
,33
,50
,51
]}

Liu, Yongmei ^{[18
]}

Maennistoe, Satu ^{[38
]}

Uitterlinden, Andre G. ^{[22
,23
]}

Deloukas, Panos ^{[34
,52
]}

Seppaelae, Ilkka ^{[45
,46
,47
]}

Psaty, Bruce M. ^{[1
,2
,4
,59
]}

机构：

[1] Univ Washington, Dept Epidemiol, Seattle, WA 98195 USA

[2] Univ Washington, Dept Med, Seattle, WA 98195 USA

[3] Univ Washington, Dept Biostat, Seattle, WA 98195 USA

[4] Univ Washington, Dept Hlth Serv, Seattle, WA 98195 USA

[5] Univ Washington, Cardiovasc Hlth Res Unit, Seattle, WA 98195 USA

[6] Baylor Coll Med, Dept Pediat, Childrens Nutr Res Ctr, USDA ARS, Houston, TX 77030 USA

[7] Univ Texas Hlth Sci Ctr Houston, Div Epidemiol Human Genet & Environm Sci, Houston, TX USA

[8] Univ St Thomas, Dept Math Comp Sci & Cooperat Engn, Houston, TX 77006 USA

[9] Boston Univ, Sch Publ Hlth, Dept Biostat, Boston, MA 02215 USA

[10] Washington Univ, Sch Med, Div Stat Gen, Dept Genet, St Louis, MO USA

[11] Harokopio Univ Athens, Dept Nutr & Dietet, Athens, Greece

[12] Lund Univ, Dept Clin Sci, Genet & Mol Epidemiol Unit, Malmo, Sweden

[13] Lund Univ, Dept Clin Sci, Malmo, Sweden

[14] Umea Univ, Dept Biobank Res, Umea, Sweden

[15] Umea Univ, Dept Odontol, Umea, Sweden

[16] Umea Univ, Dept Publ Hlth & Clin Med, Umea, Sweden

[17] Wake Forest Univ, Bowman Gray Sch Med, Dept Internal Med, Winston Salem, NC 27103 USA

[18] Wake Forest Univ, Bowman Gray Sch Med, Dept Epidemiol & Prevent, Div Publ Hlth Sci, Winston Salem, NC 27103 USA

[19] Univ Helsinki, Inst Behav Sci, Helsinki, Finland

[20] Univ Helsinki, Dept Food & Environm Sci, Helsinki, Finland

[21] Univ Helsinki, Dept Gen Practice & Primary Hlth Care, Helsinki, Finland

[22] Erasmus Univ, Med Ctr, Dept Epidemiol, Rotterdam, Netherlands

[23] Erasmus Univ, Med Ctr, Dept Internal Med, Rotterdam, Netherlands

[24] Univ Turku, Res Ctr Appl & Prevent Cardiovasc Med, Turku, Finland

[25] Harvard Univ, Sch Publ Hlth, Dept Epidemiol, Boston, MA 02115 USA

[26] Harvard Univ, Sch Publ Hlth, Dept Nutr, Boston, MA 02115 USA

[27] Harvard Univ, Sch Med, Brigham & Womens Hosp, Dept Med, Boston, MA 02115 USA

[28] Tufts Univ, Friedman Sch Nutr Sci & Policy, Boston, MA 02111 USA

[29] Univ N Carolina, Dept Epidemiol, Chapel Hill, NC USA

[30] Univ N Carolina, Carolina Ctr Genome Sci, Chapel Hill, NC USA

[31] Tufts Univ, Nutr Epidemiol Program, Boston, MA 02111 USA

[32] Tufts Univ, Jean Mayer USDA, Human Nutr Res Ctr Aging, Boston, MA 02111 USA

[33] Tufts Univ, Nutr & Genom Lab, Boston, MA 02111 USA

[34] Barts, William Harvey Res Inst, London, England

[35] Queen Mary Univ London, London Sch Med & Dent, London, England

[36] NIA, Lab Epidemiol & Populat Sci, Bethesda, MD 20892 USA

[37] NIA, Neurogenet Lab, Bethesda, MD 20892 USA

[38] Natl Inst Hlth & Welf, Dept Chron Dis Prevent, Helsinki, Finland

[39] Univ Virginia, Ctr Publ Hlth Genom, Dept Publ Hlth Sci, Div Biostat & Epidemiol, Charlottesville, VA USA

[40] Netherlands Genom Initiat, Leiden, Netherlands

[41] Turku Univ Hosp, Dept Clin Physiol & Nucl Med, FIN-20520 Turku, Finland

[42] Univ Minnesota, Div Epidemiol & Community Hlth, Minneapolis, MN USA

[43] Harbor UCLA Med Ctr, Los Angeles Biomed Res Inst, Inst Translat Genom & Populat Sci, Torrance, CA 90509 USA

[44] Univ Tampere, Dept Clin Physiol, FIN-33101 Tampere, Finland

[45] Univ Tampere, Dept Clin Chem, FIN-33101 Tampere, Finland

[46] Univ Tampere, Fimlab Labs, FIN-33101 Tampere, Finland

[47] Univ Tampere, Sch Med, FIN-33101 Tampere, Finland

[48] Univ Tampere, Tampere Univ Hosp, FIN-33101 Tampere, Finland

[49] Beth Israel Deaconess Med Ctr, Div Gen Med & Primary Care, Boston, MA 02215 USA

[50] Cardiovasc Res Ctr, Dept Epidemiol & Populat Genet, Madrid, Spain

来源：

AMERICAN JOURNAL OF CLINICAL NUTRITION | 2015年 / 102卷 / 05期

关键词：

gene-diet interaction; glucose; insulin; meat intake; diet; meta-analysis; GENOME-WIDE ASSOCIATION; CORONARY-HEART-DISEASE; C-REACTIVE PROTEIN; DIABETES-MELLITUS; SUSCEPTIBILITY LOCI; UNPROCESSED RED; OLDER-ADULTS; TYPE-2; DESIGN; OBJECTIVES;

D O I：

10.3945/ajcn.114.101238

中图分类号：

R15 [营养卫生、食品卫生]; TS201 [基础科学];

学科分类号：

100403 ;

摘要：

Background: Recent 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. Objective: We 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. Design: Fourteen 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 l) 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. Results: Processed 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 0.049-1n-pmon (95% CI: 0.035, 0.063-1n-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. Conclusion: The 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.

引用

页码：1266 / 1278

页数：13

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