Literature DB >> 29530926

Meat Cooking Methods and Risk of Type 2 Diabetes: Results From Three Prospective Cohort Studies.

Gang Liu1, Geng Zong1, Kana Wu1, Yang Hu1, Yanping Li1, Walter C Willett1,2,3, David M Eisenberg1, Frank B Hu1,2,3, Qi Sun4,2.   

Abstract

OBJECTIVE: To examine open-flame and/or high-temperature cooking (grilling/barbecuing, broiling, or roasting) and doneness preferences (rare, medium, or well done) for red meat, chicken, and fish in relation to type 2 diabetes (T2D) risk among U.S. adults who consumed animal flesh regularly (≥2 servings/week). RESEARCH DESIGN AND METHODS: The prospective studies included 52,752 women from the Nurses' Health Study (NHS) (followed during 1996-2012), 60,809 women from NHS II (followed during 2001-2013), and 24,679 men from the Health Professionals Follow-Up Study (HPFS) (followed during 1996-2012) who were free of diabetes, cardiovascular disease, and cancer at baseline. Incident cases of T2D were confirmed by validated supplementary questionnaires.
RESULTS: We documented 7,895 incident cases of T2D during 1.74 million person-years of follow-up. After multivariate adjustments including baseline BMI and total consumption of red meat, chicken, and fish, higher frequency of open-flame and/or high-temperature cooking was independently associated with an elevated T2D risk. When comparing open-flame and/or high-temperature cooking >15 times/month with <4 times/month, the pooled hazard ratio (HR) (95% CI) of T2D was 1.28 (1.18, 1.39; Ptrend <0.001). When comparing the extreme quartiles of doneness-weighted frequency of high-temperature cooking, the pooled HR (95% CI) of T2D was 1.20 (1.12, 1.28; Ptrend <0.001). These associations remained significant when red meat and chicken were examined separately. In addition, estimated intake of heterocyclic aromatic amines was also associated with an increased T2D risk.
CONCLUSIONS: Independent of consumption amount, open-flame and/or high-temperature cooking for both red meat and chicken is associated with an increased T2D risk among adults who consume animal flesh regularly.
© 2018 by the American Diabetes Association.

Entities:  

Mesh:

Year:  2018        PMID: 29530926      PMCID: PMC5911789          DOI: 10.2337/dc17-1992

Source DB:  PubMed          Journal:  Diabetes Care        ISSN: 0149-5992            Impact factor:   19.112


  39 in total

1.  Meat, Dietary Heme Iron, and Risk of Type 2 Diabetes Mellitus: The Singapore Chinese Health Study.

Authors:  Mohammad Talaei; Ye-Li Wang; Jian-Min Yuan; An Pan; Woon-Puay Koh
Journal:  Am J Epidemiol       Date:  2017-10-01       Impact factor: 4.897

2.  Physical activity and incidence of non-insulin-dependent diabetes mellitus in women.

Authors:  J E Manson; E B Rimm; M J Stampfer; G A Colditz; W C Willett; A S Krolewski; B Rosner; C H Hennekens; F E Speizer
Journal:  Lancet       Date:  1991-09-28       Impact factor: 79.321

3.  Alternative dietary indices both strongly predict risk of chronic disease.

Authors:  Stephanie E Chiuve; Teresa T Fung; Eric B Rimm; Frank B Hu; Marjorie L McCullough; Molin Wang; Meir J Stampfer; Walter C Willett
Journal:  J Nutr       Date:  2012-04-18       Impact factor: 4.798

4.  Development of a food frequency questionnaire module and databases for compounds in cooked and processed meats.

Authors:  Rashmi Sinha; Amanda Cross; Jane Curtin; Thea Zimmerman; Susanne McNutt; Adam Risch; Joanne Holden
Journal:  Mol Nutr Food Res       Date:  2005-07       Impact factor: 5.914

5.  Polycyclic aromatic hydrocarbons potentiate high-fat diet effects on intestinal inflammation.

Authors:  Ayman Khalil; Pierre-Henri Villard; Mai Anh Dao; Rémy Burcelin; Serge Champion; Francis Fouchier; Jean-Francois Savouret; Yves Barra; Eric Seree
Journal:  Toxicol Lett       Date:  2010-04-20       Impact factor: 4.372

Review 6.  Unprocessed red and processed meats and risk of coronary artery disease and type 2 diabetes--an updated review of the evidence.

Authors:  Renata Micha; Georgios Michas; Dariush Mozaffarian
Journal:  Curr Atheroscler Rep       Date:  2012-12       Impact factor: 5.113

7.  Predictors of dietary heterocyclic amine intake in three prospective cohorts.

Authors:  C Byrne; R Sinha; E A Platz; E Giovannucci; G A Colditz; D J Hunter; F E Speizer; W C Willett
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  1998-06       Impact factor: 4.254

Review 8.  Prevention and management of type 2 diabetes: dietary components and nutritional strategies.

Authors:  Sylvia H Ley; Osama Hamdy; Viswanathan Mohan; Frank B Hu
Journal:  Lancet       Date:  2014-06-07       Impact factor: 79.321

9.  Meat intake and meat preparation in relation to risk of postmenopausal breast cancer in the NIH-AARP diet and health study.

Authors:  Geoffrey C Kabat; Amanda J Cross; Yikyung Park; Arthur Schatzkin; Albert R Hollenbeck; Thomas E Rohan; Rashmi Sinha
Journal:  Int J Cancer       Date:  2009-05-15       Impact factor: 7.396

10.  2-amino-1-methyl-6-phenylimidazo(4,5-b) pyridine (PhIP) induces gene expression changes in JAK/STAT and MAPK pathways related to inflammation, diabetes and cancer.

Authors:  Lora J Rogers; Alexei G Basnakian; Mohammed S Orloff; Baitang Ning; Aiwei Yao-Borengasser; Vinay Raj; Susan Kadlubar
Journal:  Nutr Metab (Lond)       Date:  2016-08-20       Impact factor: 4.169

View more
  10 in total

1.  Plant-Based Diets for Personal, Population, and Planetary Health.

Authors:  Elena C Hemler; Frank B Hu
Journal:  Adv Nutr       Date:  2019-11-01       Impact factor: 8.701

2.  Red meat consumption, obesity, and the risk of nonalcoholic fatty liver disease among women: Evidence from mediation analysis.

Authors:  Mi Na Kim; Chun-Han Lo; Kathleen E Corey; Xiao Luo; Lu Long; Xuehong Zhang; Andrew T Chan; Tracey G Simon
Journal:  Clin Nutr       Date:  2021-12-15       Impact factor: 7.324

3.  Fried Foods, Gut Microbiota, and Glucose Metabolism.

Authors:  Lu Qi
Journal:  Diabetes Care       Date:  2021-08-20       Impact factor: 17.152

4.  Identification and epidemiological characterization of Type-2 diabetes sub-population using an unsupervised machine learning approach.

Authors:  Saptarshi Bej; Jit Sarkar; Saikat Biswas; Pabitra Mitra; Partha Chakrabarti; Olaf Wolkenhauer
Journal:  Nutr Diabetes       Date:  2022-05-27       Impact factor: 4.725

Review 5.  The Metabolic Concept of Meal Sequence vs. Satiety: Glycemic and Oxidative Responses with Reference to Inflammation Risk, Protective Principles and Mediterranean Diet.

Authors:  Niva Shapira
Journal:  Nutrients       Date:  2019-10-05       Impact factor: 5.717

6.  Can Self-Determination Explain Dietary Patterns Among Adults at Risk of or with Type 2 Diabetes? A Cross-Sectional Study in Socio-Economically Disadvantaged Areas in Stockholm.

Authors:  Nuria Güil Oumrait; Meena Daivadanam; Pilvikki Absetz; David Guwatudde; Aravinda Berggreen-Clausen; Helle Mölsted Alvesson; Jeroen De Man; Kristi Sidney Annerstedt
Journal:  Nutrients       Date:  2020-02-27       Impact factor: 5.717

7.  Influence of Different Cooking Methods on Fillet Steak Physicochemical Characteristics.

Authors:  Vinícius Lopes Borela; Ernandes Rodrigues de Alencar; Marcio Antônio Mendonça; Heesup Han; António Raposo; Antonio Ariza-Montes; Luis Araya-Castillo; Renata Puppin Zandonadi
Journal:  Int J Environ Res Public Health       Date:  2022-01-05       Impact factor: 3.390

8.  Fish Cooking Methods and Impaired Glucose Metabolism Among Japanese Workers: The Furukawa Nutrition and Health Study.

Authors:  Akiko Nanri; Ayane Takazaki; Takeshi Kochi; Masafumi Eguchi; Isamu Kabe; Tetsuya Mizoue
Journal:  Nutrients       Date:  2020-06-14       Impact factor: 5.717

9.  Meta-analysis of fish consumption and risk of pancreatic cancer in 13 prospective studies with 1.8 million participants.

Authors:  Wei Jiang; Min Wang; Hai-Zhong Jiang; Guo-Chong Chen; Yong-Fei Hua
Journal:  PLoS One       Date:  2019-09-06       Impact factor: 3.240

Review 10.  Advances in dietary pattern analysis in nutritional epidemiology.

Authors:  Christina-Alexandra Schulz; Kolade Oluwagbemigun; Ute Nöthlings
Journal:  Eur J Nutr       Date:  2021-04-25       Impact factor: 5.614

  10 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.