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Red meat consumption and risk of type 2 diabetes: 3 cohorts of US adults and an updated meta-analysis
Open accessAbstract
Background The relation between consumption of different types of red meats and risk of type 2 diabetes (T2D) remains uncertain.Objective We evaluated the association between unprocessed and processed red meat consumption and incident T2D in US adults.Design We followed 37,083 men in the Health Professionals Follow-Up Study (1986-2006), 79,570 women in the Nurses' Health Study I (1980-2008), and 87,504 women in the Nurses' Health Study II (1991-2005). Diet was assessed by validated food-frequency questionnaires, and data were updated every 4 y. Incident T2D was confirmed by a validated supplementary questionnaire.Results During 4,033,322 person-years of follow-up, we documented 13,759 incident T2D cases. After adjustment for age, BMI, and other lifestyle and dietary risk factors, both unprocessed and processed red meat intakes were positively associated with T2D risk in each cohort (all P-trend <0.001). The pooled HRs (95% CIs) for a one serving/d increase in unprocessed, processed, and total red meat consumption were 1.12 (1.08, 1.16), 1.32 (1.25, 1.40), and 1.14 (1.10, 1.18), respectively. The results were confirmed by a meta-analysis (442,101 participants and 28,228 diabetes cases): the RRs (95% CIs) were 1.19 (1.04, 1.37) and 1.51 (1.25, 1.83) for 100 g unprocessed red meat/d and for 50 g processed red meat/d, respectively. We estimated that substitutions of one serving of nuts, low-fat dairy, and whole grains per day for one serving of red meat per day were associated with a 16-35% lower risk of T2D.Conclusion Our results suggest that red meat consumption, particularly processed red meat, is associated with an increased risk of T2D.
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“Consistent with this, while a minority of individual studies suggest similar cardiovascular risk for unprocessed red meat vs. processed meats,170, 171 many other individual studies and meta-analyses support much stronger effects of processed meats, including low-fat deli meats, on CVD (Figure 6).172-174”
From Dietary and Policy Priorities for Cardiovascular Disease, Diabetes, and Obesity: A Comprehensive Review (2016) · cites this paper as [172]
In the citing paper
“Interestingly, both red and processed meats, regardless of fat content, are linked to higher incidence of diabetes, although with approximately double the risk, gram-for-gram, for processed meats than for unprocessed red meats.172, 178”
From Dietary and Policy Priorities for Cardiovascular Disease, Diabetes, and Obesity: A Comprehensive Review (2016) · cites this paper as [172]
In the citing paper
“Consistent with this, while a minority of individual studies suggest similar cardiovascular risk for unprocessed red meat vs. processed meats,170, 171 many other individual studies and meta-analyses support much stronger effects of processed meats, including low-fat deli meats, on CVD (Figure 6).172-174”
From Dietary and Policy Priorities for Cardiovascular Disease, Diabetes, and Obesity: A Comprehensive Review (2016) · cites this paper as [173]
In the citing paper
“While unprocessed red meats and butter may be relatively neutral for CHD, no studies demonstrate appreciable benefits, all meats appear to increase diabetes, and processed meats are strongly linked to CHD (see Meats, above).20, 29, 173, 178”
From Dietary and Policy Priorities for Cardiovascular Disease, Diabetes, and Obesity: A Comprehensive Review (2016) · cites this paper as [173]
In the citing paper
“Red meat consumption has consistently been associated with a higher risk of type 2 diabetes mellitus in several large cohort studies and summarized by several meta-analyses (1-3).”
From Amino acids, lipid metabolites, and ferritin as potential mediators linking red meat consumption to type 2 diabetes (2015) · cites this paper as [2]
In the citing paper
“Furthermore, the red meat-associated diabetes risk was also observed in models in which red meat was substituted by foods with a similar macronutrient content (2), suggesting the relation to be independent of macronutrient composition of the diet.”
From Amino acids, lipid metabolites, and ferritin as potential mediators linking red meat consumption to type 2 diabetes (2015) · cites this paper as [2]
In the citing paper
“Potential confounders to be included as covariates were a priori selected based on the literature on the association between red meat intake and diabetes risk (2, 3) and prior investigations in EPIC-Potsdam regarding risk factors of type 2 diabetes (5), dietary patterns (27), and determinants of metabolic profiles (28,29).”
From Amino acids, lipid metabolites, and ferritin as potential mediators linking red meat consumption to type 2 diabetes (2015) · cites this paper as [2]
In the citing paper
“Still, an elevated diabetes risk was consistently observed for both unprocessed and processed red meat (1-3).”
From Amino acids, lipid metabolites, and ferritin as potential mediators linking red meat consumption to type 2 diabetes (2015) · cites this paper as [2]
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Citations
Cites
Preferred Reporting Items for Systematic Reviews and Meta-Analyses: the PRISMA statement
Moher, D., Liberati, A., Tetzlaff, J., Altman, D. G., & for the PRISMA Group (2009) · BMJ · doi:10.1136/bmj.b2535 · Cited by 83,823
Preferred reporting items for systematic reviews and meta-analyses: the PRISMA Statement.
(2009) · PubMed Central · Cited by 44,859
Report of the Expert Committee on the Diagnosis and Classification of Diabetes Mellitus
The Expert Committee on the Diagnosis and Classification of Diabetes Mellitus* (2002) · Diabetes Care · doi:10.2337/diacare.25.2007.s5 · Cited by 10,325
IDF Diabetes Atlas: Global estimates for the prevalence of diabetes for 2015 and 2040
Ogurtsova, K., Fernandes, J. D. D. R., Huang, Y., Linnenkamp, U., Guariguata, L., Cho, N. H., Cavan, D. A., Shaw, J. E., & Makaroff, L. (2017) · Diabetes Research and Clinical Practice · doi:10.1016/j.diabres.2017.03.024 · Cited by 7,138
Report of the Expert Committee on the Diagnosis and Classification of Diabetes Mellitus
The Expert Committee on the Diagnosis and Classification of Diabetes Mellitus (1997) · Diabetes Care · doi:10.2337/diacare.20.7.1183 · Cited by 6,220
Sacks, F. M., Svetkey, L. P., Vollmer, W. M., Appel, L. J., Bray, G. A., Harsha, D., Obarzanek, E., Conlin, P. R., Miller, E. R., Simons-Morton, D. G., et al. (2001) · New England Journal of Medicine · doi:10.1056/nejm200101043440101 · Cited by 5,638
Classification and diagnosis of diabetes mellitus and other categories of glucose intolerance.
National Diabetes Data Group (1979) · Diabetes · doi:10.2337/diab.28.12.1039 · Cited by 4,909
Reproducibility and validity of a semiquantitative food frequency questionnaire
WILLETT, W. C., SAMPSON, L., STAMPFER, M. J., ROSNER, B., BAIN, C., WITSCHI, J., HENNEKENS, C. H., & SPEIZER, F. E. (1985) · American Journal of Epidemiology · doi:10.1093/oxfordjournals.aje.a114086 · Cited by 4,274
Self-citationEconomic Costs of Diabetes in the U.S. in 2002
American Diabetes Association (2003) · Diabetes Care · doi:10.2337/diacare.26.3.917 · Cited by 4,147
Diet, lifestyle, and the risk of type 2 diabetes mellitus in women.
Hu, F. B., Manson, J. E., Stampfer, M. J., Colditz, G., Liu, S., Solomon, C. G., & Willett, W. C. (2001) · New England Journal of Medicine · doi:10.1056/nejmoa010492 · Cited by 2,901
Self-citation
Cited by
Sorted by citations
Items 401–500 of 713
Jambi, H., Enani, S. M., Malibary, M., Bahijri, S., Eldakhakhny, B. M., Al-Ahmadi, J., Al-Raddadi, R. M., Ajabnoor, G., Boraie, A., & Tuomilehto, J. O. (2020) · Nutrition and Metabolic Insights · doi:10.1177/1178638820965258 · Cited by 13
Monitoring a meat-free pledge with smartphones: An experimental study
Piazza, J. R., Gregson, R., Kordoni, A., Pfeiler, T. M., Ruby, M. B., Ellis, D. A., Sahin, E., & Reith, M. (2021) · Appetite · doi:10.1016/j.appet.2021.105726 · Cited by 13
Shi, X., Lin, X., Zhu, Y., Ma, Y., Li, Y., Xu, X., Zhou, G., & Li, C. (2018) · Journal of Agricultural and Food Chemistry · doi:10.1021/acs.jafc.8b01717 · Cited by 14
Effects of prophylactic iron supplementation on outcome of nonanemic pregnant women
Asadi, N., Vafaei, H., Kasraeian, M., Yoosefi, S., Faraji, A., & Abbasi, L. (2019) · Journal of the Chinese Medical Association · doi:10.1097/jcma.0000000000000184 · Cited by 13
Casperson, S. L., Conrad, Z., Raatz, S. K., Derner, J., Roemmich, J. N., Jahns, L., & Picklo, M. J. (2020) · Meat Science · doi:10.1016/j.meatsci.2020.108225 · Cited by 13
Exploring diet associations with Covid-19 and other diseases: a Network Analysis–based approach
Toor, R., & Chana, I. (2022) · Medical & Biological Engineering & Computing · doi:10.1007/s11517-022-02505-3 · Cited by 13
Ramesh, G., Wood, A. C., Allison, M., Rich, S. S., Jensen, E. T., Chen, Y. I., Rotter, J. I., Bertoni, A. G., & Goodarzi, M. O. (2022) · Nutrition Metabolism and Cardiovascular Diseases · doi:10.1016/j.numecd.2022.03.014 · Cited by 14
Dietary patterns among Saudis with type 2 diabetes mellitus in Riyadh: A cross-sectional study
Aljahdali, A., & Bawazeer, N. M. (2022) · PLoS ONE · doi:10.1371/journal.pone.0267977 · Cited by 13
Yuan, S., He, J., Wu, S., Zhang, R., Qiao, Z., Bian, X., Wang, H., & Dou, K. (2023) · Nutrition and Diabetes · doi:10.1038/s41387-023-00232-8 · Cited by 14
Wedekind, R., Keski‐Rahkonen, P., Robinot, N. R., Viallon, V., Rothwell, J. A., Boutron‐Ruault, M., Aleksandrova, K., Wittenbecher, C., Schulze, M. B., Halkjær, J., et al. (2021) · Molecular Nutrition & Food Research · doi:10.1002/mnfr.202001141 · Cited by 13
Self-citationLuo, C., Liu, H., Wang, X., Xia, L., Huang, H., Peng, X., Xia, C., & Liu, L. (2021) · American Journal of Clinical Nutrition · doi:10.1093/ajcn/nqab102 · Cited by 13
Ecosocial food policy: improving human, animal, and planetary well-being
Helne, T., & Salonen, A. O. (2016) · Sustainability Science Practice and Policy · doi:10.1080/2052546.2016.11949231 · Cited by 13
Liang, M., Wu, J., Li, H., & Zhu, Q. (2024) · Comprehensive Reviews in Food Science and Food Safety · doi:10.1111/1541-4337.13314 · Cited by 12
Separation methods for food protein purification and analysis
Wijethunga, A. M., & Emenike, C. U. (2024) · Exploration of Foods and Foodomics · doi:10.37349/eff.2024.00043 · Cited by 12
Muschalik, C., Crutzen, R., Candel, M. J. J. M., Elfeddali, I., & de Vries, H. (2020) · Health Psychology and Behavioral Medicine · doi:10.1080/21642850.2020.1730843 · Cited by 12
Hunt, C. W., Chaturvedi, R., Brown, L., Stafford, C. E., Cauley, C. E., Goldstone, R. N., Francone, T. D., Kunitake, H., Bordeianou, L., & Ricciardi, R. (2020) · Diseases of the Colon & Rectum · doi:10.1097/dcr.0000000000001804 · Cited by 12
ALİ, A. H., Yeasmin, T., Mohamed, Y. A., Mohamud, A. I., & Mishra, P. (2021) · Journal of Istanbul Veterinary Sciences · doi:10.30704/http-www-jivs-net.815835 · Cited by 12
Mie, A., Novák, V., Andersson, M., Bügel, S., & Laursen, K. H. (2022) · Journal of Agricultural and Food Chemistry · doi:10.1021/acs.jafc.1c04418 · Cited by 12
Targeted policy intervention for reducing red meat consumption: conflicts and trade-offs
James, W. H. M., Lomax, N., Birkin, M. H., & Collins, L. (2022) · BMC Nutrition · doi:10.1186/s40795-022-00570-3 · Cited by 12
Rethinking Red Meat as a Prevention Strategy for Iron Deficiency
Agarwal, U. (2013) · ICAN Infant Child & Adolescent Nutrition · doi:10.1177/1941406413491285 · Cited by 12
Dietary management of dyslipidemia
Chopra, A. K. (2023) · Indian Heart Journal · doi:10.1016/j.ihj.2023.12.005 · Cited by 13
Xia, Q., Lan, J., Pan, Y., Wang, Y., Song, T., Yang, Y., Tian, X., Chen, L., Gu, Z., & Ding, Y. (2024) · Journal of Agricultural and Food Chemistry · doi:10.1021/acs.jafc.3c09649 · Cited by 11
Uchida, M., Park, J., Fujie, S. J., Hosomi, K., Horii, N., Watanabe, K., Sanada, K., Shinohara, Y., Mizuguchi, K., Kunisawa, J., et al. (2024) · Physiological Reports · doi:10.14814/phy2.16100 · Cited by 13
Food systems and human health and nutrition: An economic policy perspective with a focus on Africa
Pinstrup‐Andersen, P. (2012) · Cited by 11
Hashemipour, S., Esmailzadehha, N., Mohammadzadeh, M., & Ziaee, A. (2016) · Eating and Weight Disorders - Studies on Anorexia Bulimia and Obesity · doi:10.1007/s40519-015-0250-8 · Cited by 11
Springmann, M. (2019) · Elsevier eBooks · doi:10.1016/b978-0-12-811660-9.00013-8 · Cited by 13
Sali, S., Farhadnejad, H., Asghari, G., Teymoori, F., Mirmiran, P., Djazayeri, A., & Azizi, F. (2020) · Diabetology & Metabolic Syndrome · doi:10.1186/s13098-020-00596-2 · Cited by 11
Talebi, S., Ghoreishy, S. M., Ghavami, A., Sikaroudi, M. K., Nielsen, S. M., Talebi, A., & Mohammadi, H. (2023) · Nutrition Reviews · doi:10.1093/nutrit/nuad144 · Cited by 12
Kuo, M., Chen, C., Wu, F., Chen, C., Yin, Z., & Wang, C. (2020) · Health & Social Care in the Community · doi:10.1111/hsc.13241 · Cited by 10
Horikawa, C., Tsuda, K., Oshida, Y., Satoh, J., Hayashino, Y., Tajima, N., Nishimura, R., Sone, H., JDCP Study Group, Koya, D., et al. (2022) · Diabetology International · doi:10.1007/s13340-022-00575-0 · Cited by 10
Ottersen, I. S., Benningstad, N. C. G., & Kunst, J. R. (2022) · Cleaner and Responsible Consumption · doi:10.1016/j.clrc.2022.100068 · Cited by 10
Menikdiwela, K. R., Guimarães, J. P. T., Scoggin, S. O., Gollahon, L., & Moustaïd‐Moussa, N. (2022) · Nutrients · doi:10.3390/nu14132583 · Cited by 10
Zhang, K., & Wu, J. (2024) · Nutrients · doi:10.3390/nu16091334 · Cited by 10
Metabolic variation reflects dietary exposure in a multi-ethnic Asian population
Low, D. Y., Mina, T. H., Sadhu, N., Wong, K. E., Jain, P. R., Dalan, R., Ng, H. K., Xie, W., Lam, B. C. C., Tay, D., et al. (2025) · Nature Metabolism · doi:10.1038/s42255-025-01359-x · Cited by 10
The contribution of subsidized food commodities to total energy intake among US adults
Siegel, K. R., Bullard, K. M., Ali, M. K., Stein, A. D., Kahn, H. S., Mehta, N. K., Girard, A. W., Narayan, K. M. V., & Imperatore, G. (2015) · Public Health Nutrition · doi:10.1017/s1368980015002414 · Cited by 10
O’Connor, L. E., & Campbell, W. W. (2017) · Nutrition Today · doi:10.1097/nt.0000000000000225 · Cited by 10
Shah, M., & Garg, A. (2019) · Journal of Diabetes and its Complications · doi:10.1016/j.jdiacomp.2019.04.010 · Cited by 10
Detection of type II diabetes mellitus using salivary transcriptomic biomarkers
Lee, Y.-H., JOSHIPURA, K. J., Vergara, J. L., & Wong, D. T. (2012) · Genomic Medicine Biomarkers and Health Sciences · doi:10.1016/j.gmbhs.2012.03.002 · Cited by 10
Cho, Y., Cudhea, F., Park, J., Lee, J.-T., Mozaffarian, D., Singh, G. M., & Shin, M. (2016) · BMJ Open · doi:10.1136/bmjopen-2016-013283 · Cited by 10
Chronic diseases associated with meat consumption: epidemiology and mechanisms
SMET, S. D., Demeyer, D. I., & HECKE, T. V. (2018) · Wageningen Academic Publishers eBooks · doi:10.3920/978-90-8686-877-3_14 · Cited by 10
The EAT–Lancet Commission: a flawed approach? – Authors' reply
Willett, W. C., Rockström, J., & Loken, B. (2019) · The Lancet · doi:10.1016/s0140-6736(19)31910-5 · Cited by 10
Self-citationLo, Y. C., Wahlqvist, M. L., Huang, Y.-C., & Lee, M. (2016) · British Journal Of Nutrition · doi:10.1017/s0007114515005140 · Cited by 9
Kim, K., Yisahak, S., Nobles, C., Andriessen, V., DeVilbiss, E., Sjaarda, L., Al-Ohali, A., Perkins, N., & Mumford, S. (2021) · Journal of Clinical Endocrinology and Metabolism · doi:10.1210/clinem/dgab179 · Cited by 7
Abu-Halaka, D., Gover, O., Rauchbach, E., Zelber‐Sagi, S., Schwartz, B., & Tirosh, O. (2021) · Food & Function · doi:10.1039/d1fo01199e · Cited by 9
Coelho‐Júnior, H. J., Calvani, R., Picca, A., Tosato, M., Savera, G., Landi, F., & Marzetti, E. (2023) · Metabolites · doi:10.3390/metabo13030431 · Cited by 9
Pouzou, J. G., & Zagmutt, F. J. (2024) · Advances in Nutrition · doi:10.1016/j.advnut.2024.100214 · Cited by 9
Mirzababaei, A., Abaj, F., Roumi, Z., Khosroshahi, R. A., Aali, Y., Clark, C. C. T., Radmehr, M., & Mirzaei, K. (2024) · Scientific Reports · doi:10.1038/s41598-024-59097-1 · Cited by 9
Givens, D. I. (2024) · animal · doi:10.1016/j.animal.2024.101263 · Cited by 11
Metabolic Signatures of 10 Processed and Non-processed Meat Products after In Vitro Digestion
Wedekind, R., Keski‐Rahkonen, P., Robinot, N. R., Mercier, F., Engel, E., Huybrechts, I., & Scalbert, A. (2020) · Metabolites · doi:10.3390/metabo10070272 · Cited by 9
Lifestyle and glycemic health 5 years postpartum in obese and non-obese high diabetes risk women
Huvinen, E., Engberg, E., Meinilä, J. M., Tammelin, T., Kulmala, J., Heinonen, K., Bergman, P., Stach‐Lempinen, B., & Koivusalo, S. B. (2020) · Acta Diabetologica · doi:10.1007/s00592-020-01553-1 · Cited by 9
Grau, N., Mohammadifard, N., Hassannejhad, R., Haghighatdoost, F., Sadeghi, M., Talaei, M., Sajjadi, F., Mavrommatis, Y., & Sarrafzadegan, N. (2021) · International Journal of Food Sciences and Nutrition · doi:10.1080/09637486.2021.1993797 · Cited by 9
Rondanelli, M., Barrile, G. C., Cavioni, A., Donati, P., Genovese, E., Mansueto, F., Mazzola, G., Patelli, Z., Pirola, M., Razza, C., et al. (2023) · Nutrients · doi:10.3390/nu15234943 · Cited by 9
Nadeau, D. A. (2014) · The Physician and Sportsmedicine · doi:10.3810/psm.2014.11.2091 · Cited by 9
Mompeó, O., Berry, S. E., Spector, T. D., Menni, C., Mangino, M., & Gibson, R. (2020) · British Journal Of Nutrition · doi:10.1017/s000711452000495x · Cited by 9
Gardner, C. D. (2020) · American Journal of Clinical Nutrition · doi:10.1093/ajcn/nqaa385 · Cited by 9
Palmer, R. D. (2025) · Nutrition and Health · doi:10.1177/02601060251314575 · Cited by 10
Nutritional and Industrial Value of Turkey Meat "Meleagris Gallopavo": Review
Baidhani, A. M. A. A. N., & Al‐Qutaifi, H. K. (2021) · Al-Qadisiyah Journal For Agriculture Sciences · doi:10.33794/qjas.2021.132315.1016 · Cited by 8
Hong, T., Sun, F., Wang, Q., Chen, X., & Han, K. (2023) · Diabetes Obesity and Metabolism · doi:10.1111/dom.15290 · Cited by 9
Goode, J. P., Smith, K. J., Breslin, M. C., Kilpatrick, M., Dwyer, T., Venn, A., & Magnussen, C. G. (2023) · British Journal Of Nutrition · doi:10.1017/s0007114523002659 · Cited by 8
Wu, H., Yi, M.-H., Liu, B.-G., Xu, Y. L. N., Wu, Q., Liu, Y., & Lu, L.-P. (2024) · Nutrition & Metabolism · doi:10.1186/s12986-024-00780-5 · Cited by 8
Kampmann, F. B., Grunnet, L. G., Halldorsson, T. I., Bjerregaard, A. A., Granström, C., Pires, S. M., Strøm, M., Vaag, A. A., Tetens, I., & Olsen, S. F. (2018) · Journal of Developmental Origins of Health and Disease · doi:10.1017/s2040174418000910 · Cited by 8
Asghari, G., Farhadnejad, H., Teymoori, F., Emamat, H., Shahrzad, M. K., Habibi-Moeini, A. S., Mirmiran, P., & Azizi, F. (2021) · Heart Lung and Circulation · doi:10.1016/j.hlc.2021.05.091 · Cited by 8
Lin, X., Yao, H., Guo, J., Huang, Y., Wang, W., Yin, B., Li, X., Wang, T., Li, C., Xu, X., et al. (2021) · Molecular Nutrition & Food Research · doi:10.1002/mnfr.202100615 · Cited by 8
Including sustainability factors in the derivation of eater profiles of young adults in Canada
Mollaei, S., Minaker, L. M., Robinson, D. T., Lynes, J. K., & Dias, G. M. (2022) · British Food Journal · doi:10.1108/bfj-06-2022-0476 · Cited by 10
Ma, E., Ohira, T., Hirai, H., Okazaki, K., Nagao, M., Hayashi, F., Nakano, H., Suzuki, Y., Sakai, A., Takahashi, A., et al. (2022) · Nutrients · doi:10.3390/nu14224872 · Cited by 8
Cho, Y., Cudhea, F., Park, J., Mozaffarian, D., Singh, G. M., & Shin, M. (2017) · Yonsei Medical Journal · doi:10.3349/ymj.2017.58.3.540 · Cited by 9
Oxygen-Carrying Proteins in Meat and Risk of Diabetes Mellitus
Evans, W. J. (2013) · JAMA Internal Medicine · doi:10.1001/jamainternmed.2013.7399 · Cited by 8
Allman, B. R., Diaz, E. C., Williams, D. K., Turner, D., Andres, A., & Børsheim, E. (2019) · Nutrients · doi:10.3390/nu11092190 · Cited by 8
Pouladi, F., Nozari, E., Hosseinzadeh, F., & Hashemi, S. (2024) · International Journal for Vitamin and Nutrition Research · doi:10.1024/0300-9831/a000803 · Cited by 7
Willits-Smith, A. M., Taillie, L. S., Jaacks, L. M., Frank, S. M., & Grummon, A. H. (2024) · International Journal of Behavioral Nutrition and Physical Activity · doi:10.1186/s12966-024-01584-9 · Cited by 8
Chen, Z., Qian, F., Liu, B., Zong, G., Li, Y., Hu, F. B., & Sun, Q. (2025) · Diabetologia · doi:10.1007/s00125-024-06353-8 · Cited by 8
Self-citationPNPLA3 gene variation modulates diet-induced improvement in liver lipid content in type 2 diabetes
Pafili, K., Zaharia, O., Straßburger, K., Knebel, B., Herder, C., Huttasch, M., Karusheva, Y., Kabisch, S., Strom, A., Nowotny, B., et al. (2025) · Clinical Nutrition · doi:10.1016/j.clnu.2025.02.032 · Cited by 8
Marsh, K. A., Saunders, A. V., & Zeuschner, C. L. (2015) · Practice, progress, and proficiency in sustainability · doi:10.4018/978-1-4666-9553-5.ch008 · Cited by 7
Crawford, M. A., Mendoza-Vasconez, A. S., & Larsen, B. A. (2015) · Women s Health · doi:10.2217/whe.15.62 · Cited by 7
Dietary patterns and type 2 diabetes—relationship to metabolic syndrome and inflammation
Bohn, T., Samouda, H., & Alkerwi, A. (2022) · Elsevier eBooks · doi:10.1016/b978-0-12-822130-3.00014-4 · Cited by 7
Correlates of nephrolithiasis in US black women: data from the black women’s health study
D'Amico, M. J., Wason, S. E. L., & Cozier, Y. C. (2023) · Urolithiasis · doi:10.1007/s00240-022-01391-6 · Cited by 7
Polese, B., Carabotti, M., Rurgo, S., Ritieni, C., Sarnelli, G., Barbara, G., Pace, F., Cuomo, R., Annibale, B., & on behalf of REMAD Group (2023) · Nutrients · doi:10.3390/nu15092119 · Cited by 7
Le, H. T., Hong, P. L., Hoang, T. N., Thu, G. N. H., Thanh, X. L. T., Kim, C. N. T., & Vu, N. T. T. (2015) · Health · doi:10.4236/health.2015.712184 · Cited by 7
Epidemiology and Risk Factors of Type 2 Diabetes
Ley, S. H., & Meigs, J. B. (2018) · Endocrinology · doi:10.1007/978-3-319-27317-4_5-1 · Cited by 7
The Mediterranean Way of Eating
Anderson, J. J. B., & Sparling, M. C. (2014) · CRC Press eBooks · doi:10.1201/b17032 · Cited by 7
Red Meat Intake and Colorectal Cancer Risk: A Summary of Epidemiological Studies
Chan, D. S. M., Aune, D., & Norat, T. (2012) · Current Nutrition Reports · doi:10.1007/s13668-012-0035-x · Cited by 7
Asher, K. E., & Peters, P. A. (2020) · British Food Journal · doi:10.1108/bfj-04-2020-0307 · Cited by 7
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Metadata
- Authors
- Pan, A., Sun, Q., Bernstein, A. M., Schulze, M. B., Manson, J. E., Willett, W. C., & Hu, F. B.
- Affiliations
- Harvard University (US)
- Venue
- The American Journal of Clinical Nutrition
- Publisher
- Elsevier BV
- Published
- 2011-10
- Volume
- 94
- Issue
- 4
- Pages
- 1088-1096
- ISSN
- 0002-9165 (ISSN-L)
- PMC
- PMC3173026
- OpenAlex
- W1995856488
- Cited by
- 709
- References
- 75
- Citations by year
- 2026: 24 · 2025: 27 · 2024: 53 · 2023: 35 · 2022: 60 · 2021: 50 · 2020: 51 · 2019: 59 · 2018: 56 · 2017: 68 · 2016: 51 · 2015: 46 · 2014: 42 · 2013: 39 · 2012: 43
- FWCI
- 39.40
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- American Journal of Clinical Nutrition (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institutes of Health (CA 87969, CA55075)
- National Heart, Lung, and Blood Institute (K99HL098459, CA55075, CA87969)
- National Cancer Institute (CA-87969, CA-55075, P01CA087969, CA50385, R01CA050385)
- National Institute of Diabetes and Digestive and Kidney Diseases (R01DK058845, DK58845)
- Topics
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Nutritional Studies and Diet
- Physical Sciences › Environmental Science › Ecology › Agriculture Sustainability and Environmental Impact
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diet, Metabolism, and Disease
- Keywords
- red meat consumption, type 2 diabetes, processed meat, diabetes risk, dietary risk factors, nuts, low-fat dairy, whole grains, Health Professionals Follow-up Study, Nurses' Health Study
- MeSH terms
- Adult, Aged, Diabetes Mellitus, Type 2, Diet, Female, Follow-Up Studies, Food Handling, Humans, Male, Meat, Middle Aged, Prospective Studies, Surveys and Questionnaires, Risk, United States, Reproducibility of Results, Cohort Studies, Incidence
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