Nutrient Density Scoring: The essential nutrient yields of over 700 foods are ranked and adjusted for bioavailability, nutrient absorption capacity, and metabolic conversion inefficiencies!
Specialized Nutrition Scoring: Figure out the right foods for you with 30 different nutrition scores that stratify foods by a number of different dietary goals!
Custom Nutrition Scoring: Use the included Custom Score tab to help create your own personal nutrition score to plan your own ideal diet!
Diverse Nutrition Data: Custom-tailor your diet with in-depth nutrition data, including oxalates, phytates, glycemic index, glycemic load, satiety, FODMAPs, PCDAAS, price, shelf life, and over 500 polyphenolic compounds!
Hazard Profiles: Avoid potential hazards from certain nutrients and other compounds with the included hazard profile data!
Vegan-Friendly Categorization: Use the included vegan-friendly categorization to help you navigate through the best vegan options!
Keto-Friendly Categorization: Use the included keto-friendly categorization to help you navigate through the best keto options!
Grocery List: Keep expenses in check with an interactive grocery list that can intelligently estimate the cost of your grocery trip.
Nutrition Analyser: Use the included nutrition analyser to quantify the nutrient content of your food selection, and minimize anti-nutrients, hunger, calories, sugar, and more!
Meal Schedule: Schedule your meals and workouts, as well as calculate your calorie and macro requirements based on your goals and body composition!
Regular Updates: The Nutri-Dex is also regularly updated with new foods and nutrition data!
It all started when I lost my job in May, 2019. I had to figure out how I could continue to target nutrient density (ND), but also integrate a cost-saving approach to my diet. Initially, while searching for a resource that could answer my question, I was directed to Efficiency Is Everything. They take some nutrition data and stratify foods by rank divided by cost. However, their approach lacks the nuance and personalization that I would have preferred. For example, their analyzes routinely suggest that white flour, breads, and pastries come out on the top of almost every score. While it may be true that these foods provide the most nutrition for the least money, these aren't healthy foods in my estimation. They're not healthy for reasons unrelated to their nutrient content. A healthy diet has a place for those foods, absolutely. But a healthy diet is not characterized by those foods. I just didn't find their resource terribly useful for my goals.
Essentially, I wanted to stratify my most preferred foods by ND, divide it by prices relevant to my region, dust my hands off, and call it a day. Partially inspired by Mat Lalonde's AHS12 talk Nutrient Density: Sticking to the Essentials, I started by making a short list of foods that I typically eat, and sort of eyeballed their nutritional content in a nutrition-tracking tool called Cronometer. I had about 75 foods on the original list, if I recall correctly. Using a really clumsy point-system that wasn't super accurate, I assigned a score to each food on my list. The approach wasn't very sophisticated, but it didn't need to be—the spreadsheet was just going to be for my own personal use, so I didn't care if the numbers weren't arrived at using the most objective methods possible.
For price data, I took some time to go through the online inventories of several large grocery stores here in Winnipeg. My primary sources were Real Canadian Superstore, Save-On-Foods, FreshCo, Walmart, and Bulk Barn. Some price data was unavailable online, and I was actually required to take a few trips to a couple of different specialty stores. Weirder things like beef tongue and rabbit aren't commonly sold at big-box grocery stores (though I did find some cow aorta at FreshCo). So it took a while to compile this data, and it is likely most applicable to people living in my region. I don't suspect that the price of salmon is the same in Seattle, for example.
I essentially got what I wanted. In the end I had a list of foods, some rough approximation of their nutritional content, a list of prices, and a column that divided one by the other. But I wasn't quite ready to dust my hands off just yet. It had come to my attention that there was an entire community on Reddit who live for this sort of thing. Their subreddit is called EatCheapAndHealthy. I figured someone might get something out of it, so I posted it. It exploded. It was one of the most heavily upvoted and heavily discussed subjects in the history of that entire subreddit. People had no shortage of questions and suggestions. I was inspired, and I listened to every suggestion and criticism.
I realized that there is massive demand for a resource like this, and people want to be able to personalize it. People want to be able to organize foods based on their own values and goals. I decided I was going to expand the spreadsheet to include more foods, more nutrition data, and more scores. I wanted to turn this clunky piece of crap into something people could use in a very personal and practical way. I included more nutrition data, and I decided that I was actually going to generate ND scores using the most objective methods I could. I rolled my sleeves up, and I went straight to the USDA's SR28 database. This is a gigantic inventory of foods with astoundingly granular nutritional content data.
I chopped the database down to a handful of common foods (approximately 700). I then used the database to calculate my ND scores. The scores are calculated by assigning points to foods based on how many multiples of each essential nutrient a food provides relative to each individual nutrient’s DRI. This method standardizes points across all nutrients. For example, the adult DRI for calcium is 1000mg per day. If a food provides 500mg, calcium would contribute 0.5 points to the food’s score. The results for every essential nutrient in a food are summed to generate the final score. The scores are then normalized from 0 to 100, and a stratification of foods by ND is generated. At the top of the list we have veal liver, at a score of 100. At the bottom of the list we have coconut oil, at a score of 0. Left out of the scores were all non-essential nutrients and sodium. Added salt would unacceptably confound the data by creating artificially high scores for certain processed foods.
The scores are also calculated to be non-linear. If a nutrient exceeds one multiple of the RDA, that nutrient's score is calculated to the power of 0.33. This favours the overall distribution of nutrients rather than allowing one single nutrient to inflate the score. For example, brazil nuts are extremely high in selenium relative to other nutrients. If the scores are calculated exactly linearly, the sheer amount of selenium inflates brazil nuts' score unreasonably high. Applying this non-linear formula dampens this effect without applying a hard cap. This way foods can still be stratified based on absolute amounts of individual nutrients, but a much larger emphasis is placed on nutrient distribution. Basically, this formula allows the score to favour the breadth of the nutrient content of a food rather than merely the height.
Nutrient Density Score Adjustments:
No adjustments are made to vitamin B1, vitamin B2, vitamin B3, manganese, phosphorus, and potassium, due to their DRIs only representing total daily intake, or due to the nutrient having close to 100% bioavailability .
The DRI for vitamin B5 is multiplied by 2 in order to accommodate its average 50% bioavailability from food .
The DRI for plant-derived vitamin B6 is multiplied by 1.74 in order to accommodate the average ~42.5% reduction in bioavailability of pyridoxine glucoside .
The DRI for animal-derived vitamin B6 is multiplied by 1.33 in order to accommodate the average ~25% reduction in bioavailability of as a result of cooking .
The contribution of vitamin B12 is capped at 1.5mcg in order to account for the average absorption cap of ~1.5mcg per serving in healthy people .
The DRI for folate has been multiplied by 2 in order to accommodate its average 50% bioavailbility from food .
The contribution of plant-derived vitamin A (as retinol activity equivalents) is capped at 900mcg. This is to accommodate the fact that it is unlikely that the body can convert more than the DRI of vitamin A from carotenoids .
The DRI for plant-derived vitamin K, phylloquinone, is multiplied by 10 in order to accommodate its 10% bioavailability from plant foods .
The DRI for vitamin C has been multiplied by 1.25 in order to accommodate its average ~80% bioavailability .
The DRI for vitamin E has been multiplied by 4.65 in order to accommodate its average 21.5% bioavailability .
Essential Fatty Acids:
The DRIs for omega-3 and omega-6 have been recalculated to 250mg/day and 500mg/day, respectively. This better reflects our actual physiological requirements for these fatty acids as provided by their pre-elongated, animal-derived varieties .
The DRIs for plant-derived omega-3 and omega-6 have been multiplied by 6.66 in order to reflect their maximal ~15% conversion rate .
The contributions of plant-derived omega-3 and omega-6 are capped at 4.4444g before conversion rates are factored, in order to accommodate their conversion rate cap of 2% of calories per day .
The DRI for calcium has been adjusted dynamically based on the oxalate-to-calcium ratio of each food.
The DRI for plant-derived copper has been multiplied by 2.94 in order to accommodate its average ~34% bioavailability from plant foods .
The DRI for animal-derived copper has been multiplied by 2.43 in order to accommodate its average ~41% bioavailability from animal foods .
The DRI for magnesium has been multiplied by 2.85 in order to accommodate its 35% bioavailability .
The DRI for iron has been adjusted dynamically based on the phytate-to-iron ratio of each food.
The DRI for selenium has been multiplied by 1.11 in order to accommodate its 90% bioavailability .
The contribution of zinc is capped at 7mg in order to account for the average absorption cap of 7mg per serving in healthy people .
The DRI for zinc has been adjusted dynamically based on the phytate-to-zinc ratio of each food.
Essential Amino Acids:
The DRIs for all essential amino acids from non-animal sources have been multiplied by 1.492 in order to accommodate their average PDCAAS score of .67 .
All scores reflecting total protein yield of non-animal foods have been multiplied by .67 in order to accommodate the average 67% bioavailability of protein from non-animal sources .
In my estimation, this is a more accurate reflection of how these foods contribute their nutrition to the diet. If any errors or oversights can be found, please feel free to drop me a line and I'll work to correct the issues as quickly as possible!
In addition to nutritional content, ND, and price, the spreadsheet also includes data for phytate, oxalate, FODMAPs, satiety, protein digestibility, glycemic index, glycemic load, and resistant starch. Phytate and oxalate data were pulled from various sources, but mostly the FAO’s "PhyFoodComp" Phytate Database and an independent Oxalate Database I found on Google. FODMAP data was mostly collected from a freely available crowd-sourced version of the Monash FODMAP Database. Satiety data was calculated by applying a modified version of Nutrition Data’s “Fullness Factor” equation to the nutrient data in the spreadsheet. Glycemic Index information was pulled from a variety of sources, but primarily from the University of Sydney's GI Database. Data relating to polyphenols was sourced from Phenol Explorer, a freely available polyphenol database. Resistant starch data is still under construction, but data is being gathered from multiple sources on PubMed until a comprehensive resource becomes available. Protein digestibility data is also still under construction, and will likely be under construction until the FAO accepts the DIAAS as their standard protein digestibility metric and collects comprehensive data.
That sums up what I have so far. I hope you find the Nutri-Dex useful!
I'm continuing to be open to suggestions and criticisms. Any such comments can be forwarded to my email at email@example.com, or directed to my twitter, @The_Nutrivore. The more people suggest, the more useful the Cheat Sheet becomes, the more value people can get out of it. As long as there is sufficient data to be integrated, I will do my best to get it done. I will be taking a little break from working on the spreadsheet, but I promise that I will do my best to implement any suggestions that can be implemented.
Disclaimer: The information contained herein does not constitute medical advice and is for educational purposes only. Please consult with your physician before starting any new dietary protocol.
 Institute of Medicine (US) Standing Committee on the Scientific Evaluation of Dietary Reference Intakes and its Panel on Folate, Other B Vitamins, and Choline. Thiamine. National Academies Press. 1998. https://www.ncbi.nlm.nih.gov/books/NBK114331/
 Institute of Medicine (US) Standing Committee on the Scientific Evaluation of Dietary Reference Intakes and its Panel on Folate, Other B Vitamins, and Choline. Riboflavin. National Academies Press. 1998. https://www.ncbi.nlm.nih.gov/books/NBK114322/
 Institute of Medicine (US) Standing Committee on the Scientific Evaluation of Dietary Reference Intakes and its Panel on Folate, Other B Vitamins, and Choline. Niacin. National Academies Press. 1998. https://www.ncbi.nlm.nih.gov/books/NBK114304/
 Institute of Medicine. Dietary Reference Intakes for Calcium and Vitamin D. National Academies Press. 2011. https://www.ncbi.nlm.nih.gov/books/NBK56056/
 Institute of Medicine. Dietary Reference Intakes: The Essential Guide to Nutrient Requirements. Manganese. Chapter 39, page 352. 2006. https://www.nap.edu/read/11537/chapter/39
 Institute of Medicine. Dietary Reference Intakes: The Essential Guide to Nutrient Requirements. Phosphorus. Chapter 41, page 364. 2006. https://www.nap.edu/read/11537/chapter/41
 Institute of Medicine. Dietary Reference Intakes: The Essential Guide to Nutrient Requirements. Potassium. Chapter 41, page 372. 2006 https://www.nap.edu/read/11537/chapter/42
 Institute of Medicine (US) Standing Committee on the Scientific Evaluation of Dietary Reference Intakes and its Panel on Folate, Other B Vitamins, and Choline. Panthotheic Acid. National Academies Press. 1998. https://www.ncbi.nlm.nih.gov/books/NBK114311/
 Reynolds RD. Bioavailability of vitamin B-6 from plant foods. Am J Clin Nutr. September 1988. https://www.ncbi.nlm.nih.gov/pubmed/2843032
 Shibata, Keiko, Yasuyo Yasuhara, and Kazuto Yasuda. Effects of Cooking Methods on the Retention of Vitamin B6 in Foods, and the Approximate Cooking Loss in Daily Meals. J. Home Econ. Jpn. 2001. https://www.semanticscholar.org/paper/Effects-of-Cooking-Methods-on-the-Retention-of-B6-Shibata-Yasuhara/b8445e60d87753144ef856e0ae207b551aa75b9c
 Carmel R. How I treat cobalamin (vitamin B12) deficiency. Blood. September 2008. https://www.ncbi.nlm.nih.gov/pubmed/18606874
 Veronica E Ohrvik and Cornelia M Witthoft. Human Folate Bioavailability. Nutrients. April 2011. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3257685/
 Janet A Novotny, et al. β-Carotene Conversion to Vitamin A Decreases As the Dietary Dose Increases in Humans. J Nutr. May 2010. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2855261/
 Gijsbers BL, Jie KS, and Vermeer C. Effect of food composition on vitamin K absorption in human volunteers. Br J Nutr. August 1996. https://www.ncbi.nlm.nih.gov/pubmed/8813897
 Jacob RA and Sotoudeh G. Vitamin C function and status in chronic disease. Nutr Clin Care. March 2002. https://www.ncbi.nlm.nih.gov/pubmed/12134712
 Emmanuelle Reboul. Vitamin E Bioavailability: Mechanisms of Intestinal Absorption in the Spotlight. Antioxidants (Basel). December 2017. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5745505/
 Zhiying Zhang, et al. Dietary Intakes of EPA and DHA Omega-3 Fatty Acids among US Childbearing-Age and Pregnant Women: An Analysis of NHANES 2001–2014. Nutrients. April 2018. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5946201/
 Isabelle Sioen, et al. Systematic Review on N-3 and N-6 Polyunsaturated Fatty Acid Intake in European Countries in Light of the Current Recommendations – Focus on Specific Population Groups. Ann Nutr Metab. April 2017. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5452278/
 Burdge GC and Wootton SA. Conversion of alpha-linolenic acid to eicosapentaenoic, docosapentaenoic and docosahexaenoic acids in young women. Br J Nutr. October 2002. https://www.ncbi.nlm.nih.gov/pubmed/12323090
 Brian S Rett and Jay Whelan. Increasing dietary linoleic acid does not increase tissue arachidonic acid content in adults consuming Western-type diets: a systematic review. Nutr Metab (Lond). June 2011. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3132704/
 Lönnerdal B. Bioavailability of copper. Am J Clin Nutr. May 1996. https://www.ncbi.nlm.nih.gov/pubmed/8615369
 Fine KD, et al. Intestinal absorption of magnesium from food and supplements. J Clin Invest. August 1991. https://www.ncbi.nlm.nih.gov/pubmed/1864954
 Fairweather-Tait SJ, Collings R, and Hurst R. Selenium bioavailability: current knowledge and future research requirements. Am J Clin Nutr. May 2010. https://www.ncbi.nlm.nih.gov/pubmed/20200264
 Lönnerdal B. Dietary factors influencing zinc absorption. J Nutr. May 2000. https://www.ncbi.nlm.nih.gov/pubmed/10801947
 PDCAAS Wikipedia article https://en.wikipedia.org/wiki/Protein_Digestibility_Corrected_Amino_Acid_Score