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Del Carmen Fernández-Fígares Jiménez M. Plant foods, healthy plant-based diets, and type 2 diabetes: a review of the evidence. Nutr Rev 2024; 82:929-948. [PMID: 37550262 DOI: 10.1093/nutrit/nuad099] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/09/2023] Open
Abstract
Type 2 diabetes (T2D) is a metabolic chronic disease in which insulin resistance and insufficient insulin production lead to elevated blood glucose levels. The prevalence of T2D is growing worldwide, mainly due to obesity and the adoption of Western diets. Replacing animal foods with healthy plant foods is associated with a lower risk of T2D in prospective studies. In randomized controlled trials, the consumption of healthy plant foods in place of animal foods led to cardiometabolic improvements in patients with T2D or who were at high risk of the disease. Dietary patterns that limit or exclude animal foods and focus on healthy plant foods (eg, fruits, vegetables, whole grains, nuts, legumes), known as healthy, plant-based diets, are consistently associated with a lower risk of T2D in cohort studies. The aim of this review is to examine the differential effects of plant foods and animal foods on T2D risk and to describe the existing literature about the role of healthy, plant-based diets, particularly healthy vegan diets, in T2D prevention and management. The evidence from cohort studies and randomized controlled trials will be reported, in addition to the potential biological mechanisms that seem to be involved.
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Noerman S, Johansson A, Shi L, Lehtonen M, Hanhineva K, Johansson I, Brunius C, Landberg R. Fasting plasma metabolites reflecting meat consumption and their associations with incident type 2 diabetes in two Swedish cohorts. Am J Clin Nutr 2024; 119:1280-1292. [PMID: 38403167 DOI: 10.1016/j.ajcnut.2024.02.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Revised: 02/02/2024] [Accepted: 02/20/2024] [Indexed: 02/27/2024] Open
Abstract
BACKGROUND Consumption of processed red meat has been associated with increased risk of developing type 2 diabetes (T2D), but challenges in dietary assessment call for objective intake biomarkers. OBJECTIVES This study aimed to investigate metabolite biomarkers of meat intake and their associations with T2D risk. METHODS Fasting plasma samples were collected from a case-control study nested within Västerbotten Intervention Program (VIP) (214 females and 189 males) who developed T2D after a median follow-up of 7 years. Panels of biomarker candidates reflecting the consumption of total, processed, and unprocessed red meat and poultry were selected from the untargeted metabolomics data collected on the controls. Observed associations were then replicated in Swedish Mammography clinical subcohort in Uppsala (SMCC) (n = 4457 females). Replicated metabolites were assessed for potential association with T2D risk using multivariable conditional logistic regression in the discovery and Cox regression in the replication cohorts. RESULTS In total, 15 metabolites were associated with ≥1 meat group in both cohorts. Acylcarnitines 8:1, 8:2, 10:3, reflecting higher processed meat intake [r > 0.22, false discovery rate (FDR) < 0.001 for VIP and r > 0.05; FDR < 0.001 for SMCC) were consistently associated with higher T2D risk in both data sets. Conversely, lysophosphatidylcholine 17:1 and phosphatidylcholine (PC) 15:0/18:2 were associated with lower processed meat intake (r < -0.12; FDR < 0.023, for VIP and r < -0.05; FDR < 0.001, for SMCC) and with lower T2D risk in both data sets, except for PC 15:0/18:2, which was significant only in the VIP cohort. All associations were attenuated after adjustment for BMI (kg/m2). CONCLUSIONS Consistent associations of biomarker candidates involved in lipid metabolism between higher processed red meat intake with higher T2D risk and between those reflecting lower intake with the lower risk may suggest a relationship between processed meat intake and higher T2D risk. However, attenuated associations after adjusting for BMI indicates that such a relationship may at least partly be mediated or confounded by BMI.
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Affiliation(s)
- Stefania Noerman
- Division of Food and Nutrition Science, Department of Life Sciences, Chalmers University of Technology, Gothenburg, Sweden.
| | - Anna Johansson
- Division of Food and Nutrition Science, Department of Life Sciences, Chalmers University of Technology, Gothenburg, Sweden
| | - Lin Shi
- Division of Food and Nutrition Science, Department of Life Sciences, Chalmers University of Technology, Gothenburg, Sweden; School of Food Engineering and Nutritional Science, Shaanxi Normal University, Xi'an, China
| | - Marko Lehtonen
- School of Pharmacy, University of Eastern Finland, Kuopio, Finland
| | - Kati Hanhineva
- Department of Life Technologies, Food Sciences Unit, University of Turku, Turku, Finland; Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland
| | - Ingegerd Johansson
- Department of Odontology, School of Dentistry, Cariology, Umeå University, Sweden
| | - Carl Brunius
- Division of Food and Nutrition Science, Department of Life Sciences, Chalmers University of Technology, Gothenburg, Sweden
| | - Rikard Landberg
- Division of Food and Nutrition Science, Department of Life Sciences, Chalmers University of Technology, Gothenburg, Sweden
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García-Gavilán J, Nishi S, Paz-Graniel I, Guasch-Ferré M, Razquin C, Clish CB, Toledo E, Ruiz-Canela M, Corella D, Deik A, Drouin-Chartier JP, Wittenbecher C, Babio N, Estruch R, Ros E, Fitó M, Arós F, Fiol M, Serra-Majem L, Liang L, Martínez-González MA, Hu FB, Salas-Salvadó J. Plasma Metabolite Profiles Associated with the Amount and Source of Meat and Fish Consumption and the Risk of Type 2 Diabetes. Mol Nutr Food Res 2022; 66:e2200145. [PMID: 36214069 PMCID: PMC9722604 DOI: 10.1002/mnfr.202200145] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Revised: 09/12/2022] [Indexed: 01/18/2023]
Abstract
SCOPE Consumption of meat has been associated with a higher risk of type 2 diabetes (T2D), but if plasma metabolite profiles associated with these foods reflect this relationship is unknown. The objective is to identify a metabolite signature of consumption of total meat (TM), red meat (RM), processed red meat (PRM), and fish and examine if they are associated with T2D risk. METHODS AND RESULTS The discovery population includes 1833 participants from the PREDIMED trial. The internal validation sample includes 1522 participants with available 1-year follow-up metabolomic data. Associations between metabolites and TM, RM, PRM, and fish are evaluated with elastic net regression. Associations between the profiles and incident T2D are estimated using Cox regressions. The profiles included 72 metabolites for TM, 69 for RM, 74 for PRM, and 66 for fish. After adjusting for T2D risk factors, only profiles of TM (Hazard Ratio (HR): 1.25, 95% CI: 1.06-1.49), RM (HR: 1.27, 95% CI: 1.07-1.52), and PRM (HR: 1.27, 95% CI: 1.07-1.51) are associated with T2D. CONCLUSIONS The consumption of TM, its subtypes, and fish is associated with different metabolites, some of which have been previously associated with T2D. Scores based on the identified metabolites for TM, RM, and PRM show a significant association with T2D risk.
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Affiliation(s)
- Jesús García-Gavilán
- Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, Unitat de Nutrició Humana. Hospital Universitari San Joan de Reus, Reus, Spain,Institut d’Investigació Sanitària Pere Virgili (IISPV), Reus, Spain,Consorcio CIBER, Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
| | - Stephanie Nishi
- Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, Unitat de Nutrició Humana. Hospital Universitari San Joan de Reus, Reus, Spain,Institut d’Investigació Sanitària Pere Virgili (IISPV), Reus, Spain,Consorcio CIBER, Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain,Toronto 3D (Diet, Digestive Tract and Disease) Knowledge Synthesis and Clinical Trials Unit, Toronto, ON, Canada,Clinical Nutrition and Risk Factor Modification Centre, St. Michael’s Hospital, Unity Health Toronto, ON, Canada
| | - Indira Paz-Graniel
- Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, Unitat de Nutrició Humana. Hospital Universitari San Joan de Reus, Reus, Spain,Institut d’Investigació Sanitària Pere Virgili (IISPV), Reus, Spain,Consorcio CIBER, Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
| | - Marta Guasch-Ferré
- Department of Nutrition, Harvard TH Chan School of Public Health, Boston, MA, USA,Channing Division for Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Cristina Razquin
- Consorcio CIBER, Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain,Department of Preventive Medicine and Public Health, Navarra Health Research Institute (IDISNA), University of Navarra, Pamplona, Spain
| | | | - Estefanía Toledo
- Consorcio CIBER, Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain,Department of Preventive Medicine and Public Health, Navarra Health Research Institute (IDISNA), University of Navarra, Pamplona, Spain
| | - Miguel Ruiz-Canela
- Consorcio CIBER, Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain,Department of Preventive Medicine and Public Health, Navarra Health Research Institute (IDISNA), University of Navarra, Pamplona, Spain
| | - Dolores Corella
- Consorcio CIBER, Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain,Department of Preventive Medicine, University of Valencia, Valencia, Spain
| | - Amy Deik
- The Broad Institute of Harvard and MIT, Boston, MA, USA
| | - Jean-Philippe Drouin-Chartier
- Centre Nutrition, Santé et Société, Institut sur la Nutrition et les Aliments Fonctionnels, Faculté de Pharmacie, Université Laval, Québec, Canada
| | - Clemens Wittenbecher
- Toronto 3D (Diet, Digestive Tract and Disease) Knowledge Synthesis and Clinical Trials Unit, Toronto, ON, Canada,Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany,German Center for Diabetes Research, Neuherberg, Germany
| | - Nancy Babio
- Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, Unitat de Nutrició Humana. Hospital Universitari San Joan de Reus, Reus, Spain,Institut d’Investigació Sanitària Pere Virgili (IISPV), Reus, Spain,Consorcio CIBER, Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
| | - Ramon Estruch
- Consorcio CIBER, Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain,Department of Internal Medicine, Institut d’Investigacions Biomèdiques August Pi Sunyer, Hospital Clinic, University of Barcelona, Barcelona, Spain
| | - Emilio Ros
- Consorcio CIBER, Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain,Lipid Clinic, Department of Endocrinology and Nutrition, Agust Pi i Sunyer Biomedical Research Institute (IDIBAPS), Hospital Clinic, University of Barcelona, Barcelona, Spain
| | - Montserrat Fitó
- Consorcio CIBER, Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain,Cardiovascular and Nutrition Research Group, Institut de Recerca Hospital del Mar, Barcelona, Spain
| | - Fernando Arós
- Consorcio CIBER, Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain,Department of Cardiology, University Hospital of Alava, Vitoria, Spain
| | - Miquel Fiol
- Consorcio CIBER, Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain,Institute of Health Sciences IUNICS, University of Balearic Islands and Hospital Son Espases, Palma de Mallorca, Spain
| | - Lluís Serra-Majem
- Consorcio CIBER, Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain,Research Institute of Biomedical and Health Sciences IUIBS, University of Las Palmas de Gran Canaria, Las Palmas, Spain
| | - Liming Liang
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, 02115, USA,Department of Statistics, Harvard T. H. Chan School of Public Health, Boston, MA, 02115, USA
| | - Miguel A Martínez-González
- Consorcio CIBER, Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain,Department of Nutrition, Harvard TH Chan School of Public Health, Boston, MA, USA,Department of Preventive Medicine and Public Health, Navarra Health Research Institute (IDISNA), University of Navarra, Pamplona, Spain
| | - Frank B Hu
- Department of Nutrition, Harvard TH Chan School of Public Health, Boston, MA, USA,Channing Division for Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA,Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, 02115, USA
| | - Jordi Salas-Salvadó
- Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, Unitat de Nutrició Humana. Hospital Universitari San Joan de Reus, Reus, Spain,Institut d’Investigació Sanitària Pere Virgili (IISPV), Reus, Spain,Consorcio CIBER, Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
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Perraud E, Wang J, Salomé M, Huneau JF, Lapidus N, Mariotti F. Plant and Animal Protein Intakes Largely Explain the Nutritional Quality and Health Value of Diets Higher in Plants: A Path Analysis in French Adults. Front Nutr 2022; 9:924526. [PMID: 35836593 PMCID: PMC9274246 DOI: 10.3389/fnut.2022.924526] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2022] [Accepted: 05/24/2022] [Indexed: 11/22/2022] Open
Abstract
Diets higher in plants are associated with lower risks of chronic diseases. However, animal foods, which are rich in protein, are also rich in some important minerals and vitamins. Using data from a representative survey in France (INCA3, n = 1,125), we used path analyses as a mediation-like approach to decipher the importance of plant and animal proteins in the relationship between the plant-based diet index (PDI) and diet quality. We used three types of diet quality scores, namely, nutrient security, positive nutrient adequacy, and long-term mortality risk of four diet-related diseases (i.e., coronary heart disease, stroke, type 2 diabetes, and colorectal cancer). We identified positive and negative mediations, i.e., changes in plant/animal protein intake that are associated with changes in PDI, and favor or limit the association with the diet quality score. The PDI was positively associated with the risk of long-term mortality but not significantly with nutrient adequacy or nutrient security. A positive mediation by plant protein was found for all diet quality scores (specific indirect effects (SIEs) ranging from 0.04 to 0.10 SD). Conversely, the association between PDI and nutrient adequacy (but not nutrient security) was negatively mediated by animal protein intake (SIE: −0.06 SD). In further detailed models, the association between PDI and diet quality was mainly positively mediated by protein foods from the fruit-vegetables-legumes group (0.01 SD for the nutrient security and 0.02 SD for the nutrient adequacy) and whole grains (0.02 SD for the nutrient adequacy). Our data suggest that the positive impact of plant-based diets on diet quality is largely driven by higher intakes of plant protein foods, especially from fruits-vegetables-legumes and whole grains. Conversely, lower animal protein intake tends to limit the positive impact of plant-based diets on overall positive nutrient adequacy but not security. Protein sources appear critical to healthy plant-based diets.
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Affiliation(s)
- Elie Perraud
- Université Paris-Saclay, AgroParisTech, INRAE, UMR PNCA, Paris, France
| | - Juhui Wang
- Université Paris-Saclay, AgroParisTech, INRAE, UMR PNCA, Paris, France
| | - Marion Salomé
- Université Paris-Saclay, AgroParisTech, INRAE, UMR PNCA, Paris, France
| | | | - Nathanaël Lapidus
- Sorbonne Université, INSERM, Institut Pierre Louis d'Epidémiologie et de Santé Publique IPLESP, AP-HP Sorbonne Université, Public Health Department, Saint-Antoine Hospital, Paris, France
| | - François Mariotti
- Université Paris-Saclay, AgroParisTech, INRAE, UMR PNCA, Paris, France
- *Correspondence: François Mariotti
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Chen R. Age-related disparities in modifiable risk factors for diabetes in adult populations. THE LANCET. HEALTHY LONGEVITY 2021; 2:e602-e603. [DOI: 10.1016/s2666-7568(21)00214-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2021] [Accepted: 08/18/2021] [Indexed: 10/20/2022] Open
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Higher egg consumption associated with increased risk of diabetes in Chinese adults - China Health and Nutrition Survey. Br J Nutr 2021; 126:110-117. [PMID: 33028452 DOI: 10.1017/s0007114520003955] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
The association between egg consumption and diabetes is inconclusive. We aimed to examine the association between long-term egg consumption and its trajectory with diabetes in Chinese adults. A total of 8545 adults aged ≥18 years old who attended the China Health and Nutrition Survey from 1991 to 2009 were included in this analysis. Egg consumption at each survey was assessed by a 3-d 24-h recall and weighed food record methods. The consumption trajectories of eggs were modelled with the latent class group approach. Diabetes was diagnosed based on fasting blood glucose in 2009. Logistic regression was used to examine the association. The mean age of the study population was 50·9 (sd 15·1) years. About 11·1 % had diabetes in 2009. Egg consumption nearly doubled in 2009 from 16 g/d in 1991. Compared with the first quartile of egg consumption (0-9·0 g/d), the adjusted OR of diabetes for the second (9·1-20·6 g/d), third (20·7-37·5 g/d) and fourth (≥37·6 g/d) quartiles were 1·29 (95 % CI 1·03, 1·62), 1·37 (95 % CI 1·09, 1·72) and 1·25 (95 % CI 1·04, 1·64), respectively (Pfor trend = 0·029). Three trajectory groups of egg consumption were identified. Compared with group 1 (30·7 %, low baseline intake and slight increase), both group 2 (62·2 %, medium baseline intake and increase) and group 3 (7·1 %, high baseline intake and decrease) were associated with an increased OR for diabetes. The results suggested that higher egg consumption was positively associated with the risk of diabetes in Chinese adults.
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Greenberg JA, Jiang X, Tinker LF, Snetselaar LG, Saquib N, Shadyab AH. Eggs, dietary cholesterol, choline, betaine, and diabetes risk in the Women's Health Initiative: a prospective analysis. Am J Clin Nutr 2021; 114:368-377. [PMID: 33829251 PMCID: PMC8246612 DOI: 10.1093/ajcn/nqab036] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2020] [Accepted: 01/29/2021] [Indexed: 02/07/2023] Open
Abstract
BACKGROUND Epidemiological studies have been inconsistent regarding the relations between diabetes risk and the consumption of eggs and nutrients in eggs, such as choline, betaine, and cholesterol. There have been few studies among elderly women. OBJECTIVES The objective of this study was to examine associations between consumption of eggs, cholesterol, choline, and betaine and the risk of diabetes among elderly US women. METHODS Multivariable Cox regression was used with data from the prospective Women's Health Initiative. Population attributable risks were calculated. Consumption of eggs alone (not mixed in foods) and nutrients were assessed with an FFQ. Diabetes incidence was defined as the first incidence of self-reported diabetes treated with oral diabetes medication or insulin injections. RESULTS There were 46,263 women at follow-up baseline. During 13.3 y and 592,984 person-years of follow-up, there were 5480 incident diabetes cases. Higher egg, cholesterol, and choline consumption were each significantly associated with increases in diabetes risk. The associations for eggs and choline were not significant after adjustment for cholesterol consumption. The association for eggs was attenuated after adjustment for non-egg cholesterol consumption, with 1 significant HR in the top consumption quintile (≥3 eggs/wk) of 1.15 (95% CI: 1.05, 1.27; P for linear trend = 0.0001). The population attributable risks for obesity, overweight, consumption of ≥3 eggs/wk, inadequate exercise, and poor diet were 25.0 (95% CI: 22.3, 27.6), 12.8 (95% CI: 11.1, 14.5), 4.2 (95% CI: 2.3, 6.1), 3.5 (95% CI: 1.2, 5.8), and 3.1 (95% CI: 0.5, 5.7), respectively. CONCLUSIONS As egg consumption increased to ≥3 eggs/wk, there was a steady increase in diabetes risk that may have been due to the cholesterol in the eggs. The population attributable risk for ≥3 eggs/wk was far lower than that for being obese or overweight.
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Affiliation(s)
- James A Greenberg
- Department of Health and Nutrition Sciences, Brooklyn College of the City University of New York, Brooklyn, NY, USA
| | - Xinyin Jiang
- Department of Health and Nutrition Sciences, Brooklyn College of the City University of New York, Brooklyn, NY, USA
| | - Lesley F Tinker
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Linda G Snetselaar
- Department of Epidemiology, School of Public Health, University of Iowa, Iowa City, IA, USA
| | - Nazmus Saquib
- Research Unit, College of Medicine, Sulaiman Al-Rajhi Colleges, Al Bukairiyah, Saudi Arabia
| | - Aladdin H Shadyab
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California, San Diego, La Jolla, CA, USA
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Sugano M, Matsuoka R. Nutritional Viewpoints on Eggs and Cholesterol. Foods 2021; 10:494. [PMID: 33669005 PMCID: PMC7996514 DOI: 10.3390/foods10030494] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2021] [Revised: 02/20/2021] [Accepted: 02/22/2021] [Indexed: 12/17/2022] Open
Abstract
Although most current epidemiologic studies indicate no significant association between consuming one egg daily and blood cholesterol levels and cardiovascular risk, arguments still persist with a positive association. Since the diet is one of the most influential factors for this association, we illustrate characteristic features in Japanese people whose dietary pattern is distinct from that, for example, the US (United States) population. Available epidemiologic studies in healthy Japanese people show no association between consumption of one egg daily and blood cholesterol level, consistent with those observed in the US population. However, when consumption of major nutrients and food sources of cholesterol are compared to the US population, Japanese people may have an extra-reserve against the influence of eggs on cardiovascular risk markers, despite consuming relatively more eggs. Further discussion on the influence of nutrients contained in the egg and dietary pattern, including interaction with gut microbes, is necessary. In addition, special consideration at the personalized level is needed for judgment regarding dietary cholesterol not only for hypercholesterolemic patients but for hyper-responsive healthy persons. Although randomized controlled trials with long-term follow-up are required to evaluate the association between consumption of eggs and human health, available information, at least from the nutritional viewpoint, suggests that egg is a healthy and cost-efficient food worldwide.
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Affiliation(s)
- Michihiro Sugano
- Kyushu University, Fukuoka 819-0395, Japan;
- Prefectural University of Kumamoto, Kumamoto 862-8502, Japan
- Japan Egg Science Society, Tokyo 182-0002, Japan
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Gibson S, Gray J. Evaluating current egg consumption patterns: Associations with diet quality, nutrition and health status in the UK National Diet and Nutrition Survey. NUTR BULL 2020. [DOI: 10.1111/nbu.12462] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Affiliation(s)
- S. Gibson
- Registered Nutritionist Sig‐Nurture Ltd. Southampton UK
| | - J. Gray
- Registered Nutritionist London UK
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Drouin-Chartier JP, Schwab AL, Chen S, Li Y, Sacks FM, Rosner B, Manson JE, Willett WC, Stampfer MJ, Hu FB, Bhupathiraju SN. Egg consumption and risk of type 2 diabetes: findings from 3 large US cohort studies of men and women and a systematic review and meta-analysis of prospective cohort studies. Am J Clin Nutr 2020; 112:619-630. [PMID: 32453379 PMCID: PMC7458776 DOI: 10.1093/ajcn/nqaa115] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2020] [Accepted: 04/27/2020] [Indexed: 02/07/2023] Open
Abstract
BACKGROUND Whether egg consumption is associated with the risk of type 2 diabetes (T2D) remains unsettled. OBJECTIVES We evaluated the association between egg consumption and T2D risk in 3 large US prospective cohorts, and performed a systematic review and meta-analysis of prospective cohort studies. METHODS We followed 82,750 women from the Nurses' Health Study (NHS; 1980-2012), 89,636 women from the NHS II (1991-2017), and 41,412 men from the Health Professionals Follow-up Study (HPFS; 1986-2016) who were free of T2D, cardiovascular disease, and cancer at baseline. Egg consumption was assessed every 2-4 y using a validated FFQ. We used Cox proportional hazard models to estimate HRs and 95% CIs. RESULTS During a total of 5,529,959 person-years of follow-up, we documented 20,514 incident cases of T2D in the NHS, NHS II, and HPFS. In the pooled multivariable model adjusted for updated BMI, lifestyle, and dietary confounders, a 1-egg/d increase was associated with a 14% (95% CI: 7%, 20%) higher T2D risk. In random-effects meta-analysis of 16 prospective cohort studies (589,559 participants; 41,248 incident T2D cases), for each 1 egg/d, the pooled RR of T2D was 1.07 (95% CI: 0.99, 1.15; I2 = 69.8%). There were, however, significant differences by geographic region (P for interaction = 0.01). Each 1 egg/d was associated with higher T2D risk among US studies (RR: 1.18; 95% CI: 1.10, 1.27; I2 = 51.3%), but not among European (RR: 0.99; 95% CI: 0.85, 1.15; I2 = 73.5%) or Asian (RR: 0.82; 95% CI: 0.62, 1.09; I2 = 59.1%) studies. CONCLUSIONS Results from the updated meta-analysis show no overall association between moderate egg consumption and risk of T2D. Whether the heterogeneity of the associations among US, European, and Asian cohorts reflects differences in egg consumption habits warrants further investigation.This systematic review was registered at www.crd.york.ac.uk/prospero as CRD42019127860.
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Affiliation(s)
- Jean-Philippe Drouin-Chartier
- Department of Nutrition, Harvard TH Chan School of Public Health, Boston, MA, USA
- Centre for Nutrition, Health and Society (NUTRISS), Laval University, Québec, Quebec, Canada
- Institute on Nutrition and Functional Foods (INAF), Laval University, Québec, Quebec, Canada
- Faculty of Pharmacy, Laval University, Québec, Quebec, Canada
| | - Amanda L Schwab
- Department of Nutrition, Harvard TH Chan School of Public Health, Boston, MA, USA
| | - Siyu Chen
- Department of Nutrition, Harvard TH Chan School of Public Health, Boston, MA, USA
| | - Yanping Li
- Department of Nutrition, Harvard TH Chan School of Public Health, Boston, MA, USA
| | - Frank M Sacks
- Department of Nutrition, Harvard TH Chan School of Public Health, Boston, MA, USA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Bernard Rosner
- Department of Nutrition, Harvard TH Chan School of Public Health, Boston, MA, USA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Biostatistics, Harvard TH Chan School of Public Health, Boston, MA, USA
| | - JoAnn E Manson
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Preventive Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, MA, USA
| | - Walter C Willett
- Department of Nutrition, Harvard TH Chan School of Public Health, Boston, MA, USA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, MA, USA
| | - Meir J Stampfer
- Department of Nutrition, Harvard TH Chan School of Public Health, Boston, MA, USA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, MA, USA
| | - Frank B Hu
- Department of Nutrition, Harvard TH Chan School of Public Health, Boston, MA, USA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, MA, USA
| | - Shilpa N Bhupathiraju
- Department of Nutrition, Harvard TH Chan School of Public Health, Boston, MA, USA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
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11
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Meat and fish intake and type 2 diabetes: Dose-response meta-analysis of prospective cohort studies. DIABETES & METABOLISM 2020; 46:345-352. [PMID: 32302686 DOI: 10.1016/j.diabet.2020.03.004] [Citation(s) in RCA: 33] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/23/2019] [Revised: 03/20/2020] [Accepted: 03/31/2020] [Indexed: 01/10/2023]
Abstract
AIMS This meta-analysis aimed to quantitatively examine the possible associations between total meat, red meat, processed meat, poultry and fish intakes and type 2 diabetes (T2D). METHODS Relevant articles were identified in PubMed, Embase and Web of Science databases using a search time up to January 2019. Generalized least-squares trend estimations and restricted cubic spline regression models were used for analysis. RESULTS Twenty-eight articles were included in the analysis. When comparing the highest with the lowest category of meat intake, the summary relative risk of T2D was 1.33 (95% CI: 1.16-1.52) for total meat, 1.22 (95% CI: 1.16-1.28) for red meat, 1.25 (95% CI: 1.13-1.37) for processed meat, 1.00 (95% CI: 0.93-1.07) for poultry and 1.01 (95% CI: 0.93-1.10) for fish. In the dose-response analysis, each additional 100g/day of total and red meat, and 50g/day of processed meat, were found to be associated with a 36% (95% CI: 1.23-1.49), 31% (95% CI: 1.19-1.45) and 46% (95% CI: 1.26-1.69) increased risk of T2D, respectively. In addition, there was evidence of a non-linear dose-response association between processed meat and T2D (P=0.004), with the risk increasing by 30% with increasing intakes up to 30g/day. CONCLUSION Our meta-analysis has shown a linear dose-response relationship between total meat, red meat and processed meat intakes and T2D risk. In addition, a non-linear relationship of intake of processed meat with risk of T2D was detected.
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Fan M, Li Y, Wang C, Mao Z, Zhou W, Zhang L, Yang X, Cui S, Li L. Dietary Protein Consumption and the Risk of Type 2 Diabetes: ADose-Response Meta-Analysis of Prospective Studies. Nutrients 2019; 11:nu11112783. [PMID: 31731672 PMCID: PMC6893550 DOI: 10.3390/nu11112783] [Citation(s) in RCA: 31] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2019] [Revised: 11/08/2019] [Accepted: 11/12/2019] [Indexed: 12/11/2022] Open
Abstract
The relationship between dietary protein consumption and the risk of type 2 diabetes (T2D) has been inconsistent. The aim of this meta-analysis was to explore the relations between dietary protein consumption and the risk of T2D. We conducted systematic retrieval of prospective studies in PubMed, Embase, and Web of Science. Summary relative risks were compiled with a fixed effects model or a random effects model, and a restricted cubic spline regression model and generalized least squares analysis were used to evaluate the diet–T2D incidence relationship. T2D risk increased with increasing consumption of total protein and animal protein, red meat, processed meat, milk, and eggs, respectively, while plant protein and yogurt had an inverse relationship. A non-linear association with the risk for T2D was found for the consumption of plant protein, processed meat, milk, yogurt, and soy. This meta-analysis suggests that substitution of plant protein and yogurt for animal protein, especially red meat and processed meat, can reduce the risk for T2D.
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Affiliation(s)
- Mengying Fan
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou 450000, China; (M.F.); (C.W.); (Z.M.); (W.Z.); (L.Z.); (X.Y.); (S.C.)
| | - Yuqian Li
- Department of Clinical Pharmacology, School of Pharmaceutical Science, Zhengzhou University, Zhengzhou 450000, China;
| | - Chongjian Wang
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou 450000, China; (M.F.); (C.W.); (Z.M.); (W.Z.); (L.Z.); (X.Y.); (S.C.)
| | - Zhenxing Mao
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou 450000, China; (M.F.); (C.W.); (Z.M.); (W.Z.); (L.Z.); (X.Y.); (S.C.)
| | - Wen Zhou
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou 450000, China; (M.F.); (C.W.); (Z.M.); (W.Z.); (L.Z.); (X.Y.); (S.C.)
| | - Lulu Zhang
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou 450000, China; (M.F.); (C.W.); (Z.M.); (W.Z.); (L.Z.); (X.Y.); (S.C.)
| | - Xiu Yang
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou 450000, China; (M.F.); (C.W.); (Z.M.); (W.Z.); (L.Z.); (X.Y.); (S.C.)
| | - Songyang Cui
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou 450000, China; (M.F.); (C.W.); (Z.M.); (W.Z.); (L.Z.); (X.Y.); (S.C.)
| | - Linlin Li
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou 450000, China; (M.F.); (C.W.); (Z.M.); (W.Z.); (L.Z.); (X.Y.); (S.C.)
- Correspondence: ; Tel.: +86-0371-67781247; Fax: +86-0371-67781868
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13
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Sugano M. Egg and Health: Focused on the Cholesterol Issue. J JPN SOC FOOD SCI 2019. [DOI: 10.3136/nskkk.66.362] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Affiliation(s)
- Michihiro Sugano
- Professor Emeritus, Kyushu University and Prefectural University of Kumamoto and Chair, The Japan Egg Science Society
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Saande CJ, Steffes MA, Webb JL, Valentine RJ, Rowling MJ, Schalinske KL. Whole Egg Consumption Impairs Insulin Sensitivity in a Rat Model of Obesity and Type 2 Diabetes. Curr Dev Nutr 2019; 3:nzz015. [PMID: 31008440 PMCID: PMC6462456 DOI: 10.1093/cdn/nzz015] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2018] [Revised: 02/20/2019] [Accepted: 03/06/2019] [Indexed: 01/21/2023] Open
Abstract
BACKGROUND The literature regarding the relation between egg consumption and type 2 diabetes (T2D) is inconsistent and there is limited evidence pertaining to the impact of egg consumption on measures of insulin sensitivity. OBJECTIVES The aim of this study was to investigate the effect of dietary whole egg on metabolic biomarkers of insulin resistance in T2D rats. METHODS Male Zucker diabetic fatty (ZDF) rats (n = 12; 6 wk of age) and age-matched lean controls (n = 12) were randomly assigned to be fed a casein- or whole egg-based diet. At week 5 of dietary treatment, an insulin tolerance test (ITT) was performed on all rats and blood glucose was measured by glucometer. After 7 wk of dietary treatment, rats were anesthetized and whole blood was collected via a tail vein bleed. Following sedation, the extensor digitorum longus muscle was removed before and after an intraperitoneal insulin injection, and insulin signaling in skeletal muscle was analyzed by Western blot. Serum glucose and insulin were analyzed by ELISA for calculation of the homeostatic model assessment of insulin resistance (HOMA-IR). RESULTS Mean ITT blood glucose over the course of 60 min was 32% higher in ZDF rats fed the whole egg-based diet than in ZDF rats fed the casein-based diet. Furthermore, whole egg consumption increased fasting blood glucose by 35% in ZDF rats. Insulin-stimulated phosphorylation of key proteins in the insulin signaling pathway did not differ in skeletal muscle of ZDF rats fed casein- and whole egg-based diets. In lean rats, no differences were observed in insulin tolerance, HOMA-IR and skeletal muscle insulin signaling, regardless of experimental dietary treatment. CONCLUSIONS These data suggest that whole body insulin sensitivity may be impaired by whole egg consumption in T2D rats, although no changes were observed in skeletal muscle insulin signaling that could explain this finding.
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Affiliation(s)
- Cassondra J Saande
- Department of Food Science and Human Nutrition, Iowa State University, Ames, IA 50011
- Interdepartmental Graduate Program in Nutritional Sciences, Iowa State University, Ames, IA 50011
| | - Megan A Steffes
- Department of Food Science and Human Nutrition, Iowa State University, Ames, IA 50011
| | - Joseph L Webb
- Department of Food Science and Human Nutrition, Iowa State University, Ames, IA 50011
- Interdepartmental Graduate Program in Nutritional Sciences, Iowa State University, Ames, IA 50011
| | - Rudy J Valentine
- Interdepartmental Graduate Program in Nutritional Sciences, Iowa State University, Ames, IA 50011
- Department of Kinesiology, Iowa State University, Ames, IA, 50011
| | - Matthew J Rowling
- Department of Food Science and Human Nutrition, Iowa State University, Ames, IA 50011
- Interdepartmental Graduate Program in Nutritional Sciences, Iowa State University, Ames, IA 50011
| | - Kevin L Schalinske
- Department of Food Science and Human Nutrition, Iowa State University, Ames, IA 50011
- Interdepartmental Graduate Program in Nutritional Sciences, Iowa State University, Ames, IA 50011
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15
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Wang X, Son M, Meram C, Wu J. Mechanism and Potential of Egg Consumption and Egg Bioactive Components on Type-2 Diabetes. Nutrients 2019; 11:nu11020357. [PMID: 30744071 PMCID: PMC6413102 DOI: 10.3390/nu11020357] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2018] [Revised: 02/01/2019] [Accepted: 02/01/2019] [Indexed: 12/18/2022] Open
Abstract
Type-2 diabetes (T2D) is one of the major global health challenges and a substantial economic burden. Egg and egg-derived components have been indicated to possess antioxidant, anti-inflammatory, anti-hypertensive, immunomodulatory, and anti-cancer activities. However, the scientific evidence about the benefits of egg on T2D is debatable. The relationship between egg consumption and the risk of T2D from observational epidemiological studies is not consistent. Interventional clinical studies, however, provide promising evidence that egg consumption ameliorates the risk of T2D. Current research progress also indicates that some egg components and egg-derived peptides might be beneficial in the context of T2D, in terms of insulin secretion and sensitivity, oxidative stress, and inflammation, suggesting possible application on T2D management. The current review summarizes recent clinical investigations related to the influence of egg consumption on T2D risk and in vivo and in vitro studies on the effect and mechanism of egg components and egg-derived peptides on T2D.
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Affiliation(s)
- Xiaofeng Wang
- Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB T6G 2R3, Canada.
| | - Myoungjin Son
- Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB T6G 2R3, Canada.
| | - Chalamaiah Meram
- Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB T6G 2R3, Canada.
| | - Jianping Wu
- Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB T6G 2R3, Canada.
- Cardiovascular Research Centre, University of Alberta, Edmonton, AB T6G 2R3, Canada.
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