What are the aims of Food Compass?
Food Compass is a new, science-based food rating system that aims to provide consumers, policy makers, retailers, food manufacturers, and healthcare a tool to help determine the general healthfulness of different foods, beverages, mixed meals, and restaurant meals. First produced in 2021 and evaluating 58,000 products, Food Compass continues to be evaluated and improved – stay tuned for updates.
How does Food Compass compare to other food rating systems?
Several other food rating systems are now used around the world, including in Europe, the United Kingdom, Australia, New Zealand, and other nations. Many countries, for example, use these rating systems for front-of-pack labeling of packaged products.
These other systems have several strengths, but can also have some important limitations, such as:
- Giving negative points for total fat, regardless of type
- Focusing on saturated fat alone, rather than overall fat quality
- Giving negative points for total calories, regardless of the source of those calories
- Only evaluating a limited number of nutrients and food ingredients
- Focusing on added sugars alone, rather than also refined grains and starches, which results in higher scores for packaged foods rich in refined carbohydrates
- Not assessing food processing
- Not assessing beneficial nutrients like omega-3’s, flavonoids, or carotenoids
- Scoring different food categories using different mathematical algorithms, which reduces objectivity and prevents uniform scoring of many foods or meals with multiple mixed ingredients
Food Compass aims to address each of these important limitations. A first publication assessed and reported on how Food Compass compares to other major scoring systems, including Nutri-Score, Health Star Rating, and NOVA. See the Data page for some examples, and the full paper for comparative ratings of thousands of food and beverage items using these different systems.
Is Food Compass an accurate measure of the general healthfulness of foods and beverages? How would one measure that?
In published, peer-reviewed scientific papers, Food Compass has been validated against measures of a nutritious diet as well as against multiple health outcomes. In our research, we calculated an individual’s Food Compass Score (i.FCS) in a nationally representative sample of nearly 50,000 Americans. People received higher i.FCS scores when they ate more foods with higher Food Compass scores, and fewer foods with lower Food Compass scores. We found that a person’s i.FCS highly correlated with the Healthy Eating Index, a validated measure of a healthful diet. We also found that people with higher i.FCS scores had less obesity, better blood sugar control, lower blood pressure, and better blood cholesterol levels. People with higher i.FCS scores also had a lower likelihood of metabolic syndrome and cancer and a higher likelihood of optimal metabolic health. Finally, people with higher i.FCS scores had a lower risk of death from all-causes – about 7% lower risk of dying for every 10 points higher i.FCS.
Is the work on Food Compass complete?
No. While Food Compass works well across 58,000 products, there are still exceptions where its scoring algorithm can be improved. We continue to refine and improve Food Compass based on our research, the latest science, and feedback from the scientific community. See our versions page and current work page for more information. We believe the evidence supports Food Compass as the best overall food rating system available today, working very well on average across thousands of different foods, beverages, and mixed meals. But, it can be further improved to work even better, and we are working on that now.
How should Food Compass be used in practice?
Food Compass is intended to help individuals and organizations shift towards healthier diets. It should be used in the context of other guidelines and personal goals to compare otherwise similar foods in terms of their overall contribution to health.
Individuals can use Food Compass as a convenient summary of the scientific evidence when choosing between seemingly similar foods. Scores refer to foods as consumed, so you can look for higher-scoring ways of preparing your favorite ingredients such as eggs or pasta. Food Compass also includes many packaged and branded foods, so you can use scores to shop for healthier items within each category such as higher-scoring breakfast cereals. While Food Compass works well across thousands of products on average, scores may not yet be ideal to compare foods that play very different roles in the diet, such as a protein-rich food like eggs, meat, or fish versus a carbohydrate-rich food like bread, pasta, rice, pasta, or potatoes.
Organizations can use Food Compass to improve the healthfulness of the foods they provide, by raising the average score of what they offer. In this context, each item’s score would be multiplied by the quantity bought or sold, to track increasing use of higher-scoring foods over time. In some cases, it might also be helpful to use Food Compass as part of guidance to consumers on front-of-shelf signage, front-of-pack labels, or shopping and meal planning software, again in an effort to improve average scores in each product category.
The Food Compass is a new kind of scoring system, and more research is needed on how it might be used in different settings. To focus on comparisons among otherwise similar foods, scores might be presented only in relative terms within categories, such as the top third, middle third or bottom third among a group of items that could substitute for each other. More generally, the 0-100 scores might be converted to traffic lights (green, yellow, red) or numbers of stars, and combined with other inputs such as from dietary guidelines and personal dietary preferences.
What if I follow a special diet?
If you follow a special diet, for example DASH, Mediterranean, vegetarian, vegan, low-carb, keto, paleo, low-fat, or others, then Food Compass can help you select foods within your overall preferences that are more or less likely to contribute to your health and well-being.
Is Food Compass intended for patients with diabetes or other medical conditions?
Right now, Food Compass is designed for general guidance for the overall population. In the future, we hope we might be able to produce science-based versions for specific disease conditions, such as for diabetes or obesity.
On social media, I have seen graphics showing certain breakfast cereals scoring higher than eggs, cheese, or meat. Did Tufts create these graphics?
No. Food Compass works very well, on average, across thousands of food and beverage products. But, when this number and diversity of products are scored, there are always some exceptions. These graphs were created by others to show these exceptions, rather than to show the overall performance of Food Compass and the many other foods for which Food Compass works well. But, as objective scientists, we accept constructive criticism and are using this to further improve Food Compass. We are working on an updated version now – see our versions page for more information.
How do Food Compass scores compare for breakfast cereals and breads vs. foods like eggs, cheeses, and unprocessed meats?
Because Food Compass is one of the only food rating systems to give negative points for refined carbohydrates and for food processing, breakfast cereals and breads that are rich in refined grains generally get low scores – lower than the scores for most eggs, cheeses, or unprocessed meats. We believe this is major advance, as starchy, processed cereals often receive high scores in other food rating systems. Food Compass also gives negative points for added sugars, as do most other systems.
Food Compass gives positive points for whole grains, fiber, and a lower carbohydrate-to-fiber ratio (a measure of the overall balance of refined grains and sugars vs. whole grains and bran). Whole grains and dietary fiber contain many nutrients, serve as prebiotics for the gut microbiome, and are linked to many positive health outcomes.* Breakfast cereals and breads that are rich in whole grains, fiber, and other nutrients and have no added sugar generally get high Food Compass scores, even when they’re processed. Breakfast cereals and breads that are rich in whole grains, fiber, and other nutrients but also have some added sugar generally get intermediate Food Compass scores. Breakfast cereals and breads that are rich in refined grains, with or without added sugar, generally get low Food Compass scores. We are currently evaluating whether Food Compass can be further improved to better assess the overall healthfulness of these different foods.
The Food Compass system also includes negative processing points for artificial colorings, artificial flavorings, and corn syrup. But, data on these additives were not available in the USDA Food and Nutrient Database for Dietary Studies (FNDDS), the dataset used for our research to-date. So, foods containing these additives should score lower than calculated in our current scoring summaries, and we hope to obtain and add such data in future work.
Why does Food Compass score many animal-source foods higher than many plant-based foods?
The scientific evidence actually doesn’t strongly support making nutritional distinctions based on just the plant or animal origin of a food. Animal products like fish, yogurt, and poultry can be quite healthy, other minimally processed animal products like eggs, cheese, and unprocessed red meat are often fine in moderation, and other animal products like processed meats should be minimized. Similarly, plant-based foods can vary widely in healthfulness based on their contents of whole grains, fiber, protein, and other nutrients, and on their processing characteristics and additives. For example, Food Compass scores for white bread, white rice, and refined starch breakfast cereals are generally much lower than for most minimally processed animal products.
Does Food Compass account for food processing?
Yes. Food Compass is one of the only food rating systems that includes measures of food processing along with food ingredients, nutrients, and other factors. For example, Food Compass gives negative points for ultraprocessing (as determined by the NOVA classification system) and positive points for fermentation (which has been associated in some studies with health benefits). We believe a system that combines different aspects of food processing with other factors can best assess the overall health effects of foods.
Why is there so much variation in scores for different egg, poultry, fish, and red meat products?
The calculated scores are based on a nationally representative sample of food products as actually eaten by Americans. These products are evaluated “as consumed” – not always “as purchased” in the grocery store. So, the Food Compass score for a given egg product reflects not just the eggs, but also the cooking and preparation methods: for example, the salt added, type of fat used, other ingredients (veggies, cheese, etc.), and so on. The same is true for poultry, fish, and red meat products.
We are working on scoring a much larger database of food and beverage products “as purchased” in the grocery store. Stay tuned for these scores. In the meantime, you can look for the scores for raw eggs or fish in the current dataset to see how these might score “as purchased.”
Are naturally occurring vs. fortified vitamins and minerals scored differently?
Not yet. It might be helpful to score naturally occurring vs. fortified vitamins and minerals separately. However, current food composition databases don’t allow this discrimination for most nutrients, making this a potential priority for companies to report on in the future.
Will Food Compass work perfectly for every product?
As described above and in our published scientific papers, Food Compass works very well, on average, across thousands and thousands of products. Food Compass is based on 54 attributes of each item, selected based on the strength of scientific evidence for their average effects on human health. Food Compass maps these attributes across 9 distinct dimensions, like the points of a compass, and then combines these dimensions into a single score for overall contribution to a healthy diet. We aimed to make the scoring system as accurate and consistent as possible, based on the best available science, for the largest number of foods, beverages, and mixed meals. There will always be exceptions, where Food Compass may not work as well. We are now refining and improving Food Compass based on our research, the latest science, and feedback from the scientific community. Stay tuned for updates.
Food Compass is a new, science-based food rating system that aims to provide consumers, policy makers, retailers, food manufacturers, and healthcare a tool to help determine the general healthfulness of different foods, beverages, mixed meals, and restaurant meals. First produced in 2021 and evaluating 58,000 products, Food Compass continues to be evaluated and improved – stay tuned for updates.
Several other food rating systems are now used around the world, including in Europe, the United Kingdom, Australia, New Zealand, and other nations. Many countries, for example, use these rating systems for front-of-pack labeling of packaged products.
These other systems have several strengths, but can also have some important limitations, such as:
- Giving negative points for total fat, regardless of type
- Focusing on saturated fat alone, rather than overall fat quality
- Giving negative points for total calories, regardless of the source of those calories
- Only evaluating a limited number of nutrients and food ingredients
- Focusing on added sugars alone, rather than also refined grains and starches, which results in higher scores for packaged foods rich in refined carbohydrates
- Not assessing food processing
- Not assessing beneficial nutrients like omega-3’s, flavonoids, or carotenoids
- Scoring different food categories using different mathematical algorithms, which reduces objectivity and prevents uniform scoring of many foods or meals with multiple mixed ingredients
Food Compass aims to address each of these important limitations. A first publication assessed and reported on how Food Compass compares to other major scoring systems, including Nutri-Score, Health Star Rating, and NOVA. See the Data page for some examples, and the full paper for comparative ratings of thousands of food and beverage items using these different systems.
In published, peer-reviewed scientific papers, Food Compass has been validated against measures of a nutritious diet as well as against multiple health outcomes. In our research, we calculated an individual’s Food Compass Score (i.FCS) in a nationally representative sample of nearly 50,000 Americans. People received higher i.FCS scores when they ate more foods with higher Food Compass scores, and fewer foods with lower Food Compass scores. We found that a person’s i.FCS highly correlated with the Healthy Eating Index, a validated measure of a healthful diet. We also found that people with higher i.FCS scores had less obesity, better blood sugar control, lower blood pressure, and better blood cholesterol levels. People with higher i.FCS scores also had a lower likelihood of metabolic syndrome and cancer and a higher likelihood of optimal metabolic health. Finally, people with higher i.FCS scores had a lower risk of death from all-causes – about 7% lower risk of dying for every 10 points higher i.FCS.
No. While Food Compass works well across 58,000 products, there are still exceptions where its scoring algorithm can be improved. We continue to refine and improve Food Compass based on our research, the latest science, and feedback from the scientific community. See our versions page and current work page for more information. We believe the evidence supports Food Compass as the best overall food rating system available today, working very well on average across thousands of different foods, beverages, and mixed meals. But, it can be further improved to work even better, and we are working on that now.
Food Compass is intended to help individuals and organizations shift towards healthier diets. It should be used in the context of other guidelines and personal goals to compare otherwise similar foods in terms of their overall contribution to health.
Individuals can use Food Compass as a convenient summary of the scientific evidence when choosing between seemingly similar foods. Scores refer to foods as consumed, so you can look for higher-scoring ways of preparing your favorite ingredients such as eggs or pasta. Food Compass also includes many packaged and branded foods, so you can use scores to shop for healthier items within each category such as higher-scoring breakfast cereals. While Food Compass works well across thousands of products on average, scores may not yet be ideal to compare foods that play very different roles in the diet, such as a protein-rich food like eggs, meat, or fish versus a carbohydrate-rich food like bread, pasta, rice, pasta, or potatoes.
Organizations can use Food Compass to improve the healthfulness of the foods they provide, by raising the average score of what they offer. In this context, each item’s score would be multiplied by the quantity bought or sold, to track increasing use of higher-scoring foods over time. In some cases, it might also be helpful to use Food Compass as part of guidance to consumers on front-of-shelf signage, front-of-pack labels, or shopping and meal planning software, again in an effort to improve average scores in each product category.
The Food Compass is a new kind of scoring system, and more research is needed on how it might be used in different settings. To focus on comparisons among otherwise similar foods, scores might be presented only in relative terms within categories, such as the top third, middle third or bottom third among a group of items that could substitute for each other. More generally, the 0-100 scores might be converted to traffic lights (green, yellow, red) or numbers of stars, and combined with other inputs such as from dietary guidelines and personal dietary preferences.
If you follow a special diet, for example DASH, Mediterranean, vegetarian, vegan, low-carb, keto, paleo, low-fat, or others, then Food Compass can help you select foods within your overall preferences that are more or less likely to contribute to your health and well-being.
Right now, Food Compass is designed for general guidance for the overall population. In the future, we hope we might be able to produce science-based versions for specific disease conditions, such as for diabetes or obesity.
No. Food Compass works very well, on average, across thousands of food and beverage products. But, when this number and diversity of products are scored, there are always some exceptions. These graphs were created by others to show these exceptions, rather than to show the overall performance of Food Compass and the many other foods for which Food Compass works well. But, as objective scientists, we accept constructive criticism and are using this to further improve Food Compass. We are working on an updated version now – see our versions page for more information.
Because Food Compass is one of the only food rating systems to give negative points for refined carbohydrates and for food processing, breakfast cereals and breads that are rich in refined grains generally get low scores – lower than the scores for most eggs, cheeses, or unprocessed meats. We believe this is major advance, as starchy, processed cereals often receive high scores in other food rating systems. Food Compass also gives negative points for added sugars, as do most other systems.
Food Compass gives positive points for whole grains, fiber, and a lower carbohydrate-to-fiber ratio (a measure of the overall balance of refined grains and sugars vs. whole grains and bran). Whole grains and dietary fiber contain many nutrients, serve as prebiotics for the gut microbiome, and are linked to many positive health outcomes.* Breakfast cereals and breads that are rich in whole grains, fiber, and other nutrients and have no added sugar generally get high Food Compass scores, even when they’re processed. Breakfast cereals and breads that are rich in whole grains, fiber, and other nutrients but also have some added sugar generally get intermediate Food Compass scores. Breakfast cereals and breads that are rich in refined grains, with or without added sugar, generally get low Food Compass scores. We are currently evaluating whether Food Compass can be further improved to better assess the overall healthfulness of these different foods.
The Food Compass system also includes negative processing points for artificial colorings, artificial flavorings, and corn syrup. But, data on these additives were not available in the USDA Food and Nutrient Database for Dietary Studies (FNDDS), the dataset used for our research to-date. So, foods containing these additives should score lower than calculated in our current scoring summaries, and we hope to obtain and add such data in future work.
The scientific evidence actually doesn’t strongly support making nutritional distinctions based on just the plant or animal origin of a food. Animal products like fish, yogurt, and poultry can be quite healthy, other minimally processed animal products like eggs, cheese, and unprocessed red meat are often fine in moderation, and other animal products like processed meats should be minimized. Similarly, plant-based foods can vary widely in healthfulness based on their contents of whole grains, fiber, protein, and other nutrients, and on their processing characteristics and additives. For example, Food Compass scores for white bread, white rice, and refined starch breakfast cereals are generally much lower than for most minimally processed animal products.
Yes. Food Compass is one of the only food rating systems that includes measures of food processing along with food ingredients, nutrients, and other factors. For example, Food Compass gives negative points for ultraprocessing (as determined by the NOVA classification system) and positive points for fermentation (which has been associated in some studies with health benefits). We believe a system that combines different aspects of food processing with other factors can best assess the overall health effects of foods.
The calculated scores are based on a nationally representative sample of food products as actually eaten by Americans. These products are evaluated “as consumed” – not always “as purchased” in the grocery store. So, the Food Compass score for a given egg product reflects not just the eggs, but also the cooking and preparation methods: for example, the salt added, type of fat used, other ingredients (veggies, cheese, etc.), and so on. The same is true for poultry, fish, and red meat products.
We are working on scoring a much larger database of food and beverage products “as purchased” in the grocery store. Stay tuned for these scores. In the meantime, you can look for the scores for raw eggs or fish in the current dataset to see how these might score “as purchased.”
Not yet. It might be helpful to score naturally occurring vs. fortified vitamins and minerals separately. However, current food composition databases don’t allow this discrimination for most nutrients, making this a potential priority for companies to report on in the future.
As described above and in our published scientific papers, Food Compass works very well, on average, across thousands and thousands of products. Food Compass is based on 54 attributes of each item, selected based on the strength of scientific evidence for their average effects on human health. Food Compass maps these attributes across 9 distinct dimensions, like the points of a compass, and then combines these dimensions into a single score for overall contribution to a healthy diet. We aimed to make the scoring system as accurate and consistent as possible, based on the best available science, for the largest number of foods, beverages, and mixed meals. There will always be exceptions, where Food Compass may not work as well. We are now refining and improving Food Compass based on our research, the latest science, and feedback from the scientific community. Stay tuned for updates.
* In randomized controlled trials, consumption of whole grain foods improves glucose-insulin control, LDL cholesterol, and possibly vascular function and inflammation;1 while dietary fiber reduces blood pressure and LDL cholesterol. Consistent with these benefits, intake of foods containing whole grains or dietary fiber is associated in long-term observational studies with lower risk of long-term weight gain, diabetes, coronary heart disease, and certain cancers.2-5
In contrast, intakes of refined grains, starches, and added sugars are associated with adverse health outcomes, including long-term weight gain, diabetes, and coronary heart disease.6-9 Metabolic feeding studies confirm harms of refined carbohydrates,10 while clinical trials demonstrate weight loss and improved blood sugar control on diets that reduce refined carbohydrates and glycemic load.11-13 For foods containing a mix of grains and/or sugars, the ratio of total carbohydrate to fiber provides one useful measure of healthfulness, aiming to balance the relative proportions of whole grains, bran, refined starch, and sugars.14-17 Food Compass incorporates each of these factors, including contents of whole grain, dietary fiber, added sugar, and the ratio of carbohydrate to fiber; as well as other factors like protein, sodium, vitamins and minerals, degree of processing, and more.
In contrast to evidence for benefits of whole grains and dietary fiber and harms of refined starches and sugars, the current science suggests that minimally processed animal products are generally neutral for major health endpoints. In prospective observational studies, intakes of eggs and poultry are generally not associated with risk of cardiovascular events, diabetes, or cancers.5,18-21 In a few studies among patients who already have diabetes, eating eggs and dietary cholesterol is linked to higher risk of cardiovascular events, suggesting a potential interaction for cardiovascular endpoints between insulin resistance and dietary cholesterol, but more research is needed on this. In some long-term observational cohorts, cheese intake associates with modestly lower risk of stroke and diabetes; in other studies it appears more neutral.22-24 Dairy consumption is linked to higher risk of certain cancers.5
Intake of processed meats (i.e., red meat or poultry preserved with sodium or other additives) is associated with higher risk of heart disease, stroke, and diabetes, while unprocessed red meats are associated with higher risk of diabetes but have generally smaller associations with cardiovascular events.19,25,26 The high salt content, and possibly other preservatives like nitrites, in processed meats likely contribute to the higher risk of cardiovascular events.27 Heme iron, a risk factor for diabetes in animal experiments, gestational diabetes, and inborn errors of iron metabolism such as hemochromatosis, may also partly explain the higher risk of diabetes seen with both processed and unprocessed red meats.28-30 Red meat consumption is also associated with higher risk of cancer, in particular colorectal cancer.5 Red meats are also sources of nutrients, like protein, vitamin B12, and zinc. Food Compass incorporates and balances these various characteristics, including amounts of red meat, protein, vitamins, salt, nitrates, and processing, among other attributes.
1. Ye EQ, Chacko SA, Chou EL, Kugizaki M, Liu S. Greater whole-grain intake is associated with lower risk of type 2 diabetes, cardiovascular disease, and weight gain. J Nutr. 2012;142(7):1304-1313.
2. Mozaffarian D. Dietary and Policy Priorities for Cardiovascular Disease, Diabetes, and Obesity: A Comprehensive Review. Circulation. 2016;133(2):187-225.
3. Micha R, Shulkin ML, Penalvo JL, et al. Etiologic effects and optimal intakes of foods and nutrients for risk of cardiovascular diseases and diabetes: Systematic reviews and meta-analyses from the Nutrition and Chronic Diseases Expert Group (NutriCoDE). PLoS One. 2017;12(4):e0175149.
4. Weickert MO, Pfeiffer AFH. Impact of Dietary Fiber Consumption on Insulin Resistance and the Prevention of Type 2 Diabetes. The Journal of nutrition. 2018;148(1):7-12.
5. World Cancer Research Fund/ American Institute for Cancer Research. Continuous Update Project (CUP).
6. Livesey G, Taylor R, Livesey HF, et al. Dietary Glycemic Index and Load and the Risk of Type 2 Diabetes: A Systematic Review and Updated Meta-Analyses of Prospective Cohort Studies. Nutrients. 2019;11(6).
7. Mozaffarian D, Hao T, Rimm EB, Willett WC, Hu FB. Changes in diet and lifestyle and long-term weight gain in women and men. N Engl J Med. 2011;364(25):2392-2404.
8. Tang G, Wang D, Long J, Yang F, Si L. Meta-analysis of the association between whole grain intake and coronary heart disease risk. Am J Cardiol. 2015;115(5):625-629.
9. Aune D, Norat T, Romundstad P, Vatten LJ. Whole grain and refined grain consumption and the risk of type 2 diabetes: a systematic review and dose-response meta-analysis of cohort studies. Eur J Epidemiol. 2013;28(11):845-858.
10. Ludwig DS. Aways Hungry? New York: Grand Central Life and Style; 2016.
11. Tobias DK, Chen M, Manson JE, Ludwig DS, Willett W, Hu FB. Effect of low-fat diet interventions versus other diet interventions on long-term weight change in adults: a systematic review and meta-analysis. Lancet Diabetes Endocrinol. 2015;3(12):968-979.
12. Viana LV, Gross JL, Azevedo MJ. Dietary intervention in patients with gestational diabetes mellitus: a systematic review and meta-analysis of randomized clinical trials on maternal and newborn outcomes. Diabetes Care. 2014;37(12):3345-3355.
13. Huntriss R, Campbell M, Bedwell C. The interpretation and effect of a low-carbohydrate diet in the management of type 2 diabetes: a systematic review and meta-analysis of randomised controlled trials. Eur J Clin Nutr. 2018;72(3):311-325.
14. Mozaffarian RS, Lee RM, Kennedy MA, Ludwig DS, Mozaffarian D, Gortmaker SL. Identifying whole grain foods: a comparison of different approaches for selecting more healthful whole grain products. Public Health Nutr. 2013;16(12):2255-2264.
15. Fontanelli MM, Micha R, Sales CH, Liu J, Mozaffarian D, Fisberg RM. Application of the </= 10:1 carbohydrate to fiber ratio to identify healthy grain foods and its association with cardiometabolic risk factors. Eur J Nutr. 2019.
16. Ghodsian B, Madden AM. Evaluating the </=10:1 wholegrain criterion in identifying nutrient quality and health implications of UK breads and breakfast cereals. Public Health Nutr. 2018;21(6):1186-1193.
17. Liu J, Rehm CD, Shi P, McKeown NM, Mozaffarian D, Micha R. A comparison of different practical indices for assessing carbohydrate quality among carbohydrate-rich processed products in the US. PLoS One. 2020;15(5):e0231572.
18. Abete I, Romaguera D, Vieira AR, Lopez de Munain A, Norat T. Association between total, processed, red and white meat consumption and all-cause, CVD and IHD mortality: a meta-analysis of cohort studies. Br J Nutr. 2014;112(5):762-775.
19. Yang X, Li Y, Wang C, et al. Meat and fish intake and type 2 diabetes: Dose-response meta-analysis of prospective cohort studies. Diabetes Metab. 2020.
20. Drouin-Chartier JP, Schwab AL, Chen S, et al. 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.
21. Drouin-Chartier JP, Chen S, Li Y, et al. Egg consumption and risk of cardiovascular disease: three large prospective US cohort studies, systematic review, and updated meta-analysis. BMJ. 2020;368:m513.
22. Pimpin L, Wu JH, Haskelberg H, Del Gobbo L, Mozaffarian D. Is Butter Back? A Systematic Review and Meta-Analysis of Butter Consumption and Risk of Cardiovascular Disease, Diabetes, and Total Mortality. PLoS One. 2016;11(6):e0158118.
23. Mishali M, Prizant-Passal S, Avrech T, Shoenfeld Y. Association between dairy intake and the risk of contracting type 2 diabetes and cardiovascular diseases: a systematic review and meta-analysis with subgroup analysis of men versus women. Nutrition Reviews. 2019;77(6):417-429.
24. Sluijs I, Forouhi NG, Beulens JW, et al. The amount and type of dairy product intake and incident type 2 diabetes: results from the EPIC-InterAct Study. Am J Clin Nutr. 2012;96(2):382-390.
25. Kim K, Hyeon J, Lee SA, et al. Role of Total, Red, Processed, and White Meat Consumption in Stroke Incidence and Mortality: A Systematic Review and Meta-Analysis of Prospective Cohort Studies. J Am Heart Assoc. 2017;6(9).
26. Zeraatkar D, Han MA, Guyatt GH, et al. Red and Processed Meat Consumption and Risk for All-Cause Mortality and Cardiometabolic Outcomes: A Systematic Review and Meta-analysis of Cohort Studies. Ann Intern Med. 2019;171(10):703-710.
27. Micha R, Michas G, Mozaffarian D. Unprocessed red and processed meats and risk of coronary artery disease and type 2 diabetes–an updated review of the evidence. Curr Atheroscler Rep. 2012;14(6):515-524.
28. Micha R, Michas G, Mozaffarian D. Unprocessed red and processed meats and risk of coronary artery disease and type 2 diabetes–an updated review of the evidence. Curr Athero Rep. 2012;14(6):515-524.
29. Fernandez-Real JM, McClain D, Manco M. Mechanisms Linking Glucose Homeostasis and Iron Metabolism Toward the Onset and Progression of Type 2 Diabetes. Diabetes care. 2015;38(11):2169-2176.
30. Wang X, Fang X, Wang F. Pleiotropic actions of iron balance in diabetes mellitus. Reviews in endocrine & metabolic disorders. 2015;16(1):15-23.