This serves as a basic introduction to primary scientific principles that guide our data-based personalization.
The Rootine approach combines nutritionally relevant data from your lifestyle choices, DNA (genetics), and blood values to create a unique nutrient profile for you.
The Data We Use
Each type of data plays a role in determining your unique nutrient needs. Data points are used to contextualize each other and build a model to determine the type and amount of each nutrient to meet your ideal daily intake.
Lifestyle: Our 19-question analysis provides information about your size, age, weight, biological gender, activity level, dietary preferences, family life, and more. This data is used directionally to create your baseline range for each nutrient.
- Example: If you eat a vegan diet, we know you likely need more vitamin B12.1, 2, 3
- Example: If you avoid dairy, we know you likely need more calcium.4, 5, 6
- Example: If you are a female and have a heavy menstrual flow, we know you likely need more iron.7, 8, 9
DNA: The science of nutrigenetics details how slight variations in your genes can alter how you absorb, metabolize, distribute, and excrete nutrients, thus impacting the type and amount of each nutrient you need. We assess 50+ of these variations and layer the impact into your profile.
- Example: A variation in the NQO1 gene makes your body less efficient at activating CoQ10. We correct by increasing other antioxidants in your formula.10, 11, 12, 13, 14
- Example: A variation in the VDR gene makes vitamin D bind less efficiently to its receptor. We correct by increasing your vitamin D to achieve a normal level of receptor activation.15, 16, 17, 18, 19
- Blood: Blood nutrient levels have long been the gold standard in recommending supplements and guiding dose. Changes (or lack of positive change) over recurrent blood tests is also used to determine if the dose needs further increase, a decrease, or if it is at the ideal amount.
How We Interpret The Data
We combine peer-reviewed research with clinical expertise to create the data modeling (i.e. algorithm) that generates the bespoke formulas.
In some cases, the analytics process is straightforward; If a user’s blood value of vitamin D is too low ⮕ increase the amount in their formula.
In other scenarios, it is far more complex; the user is a male, vegan, and indicates low energy ⮕ likely indicates an increased need for iron; however, the user has a double HFE gene mutation which makes supplemental iron poisonous ⮕ remove all iron from the formula.
Overall, our science team utilizes scientific research (and our PhDs) + clinical experience (from our MDs, DOs, RDs, and PharmDs,) + sound logic to combine the numerous points of data that influence the final recommended dose for each nutrient.
- Pawlak R, Parrott SJ, Raj S, Cullum-Dugan D, Lucus D. How prevalent is vitamin B(12) deficiency among vegetarians? Nutr Rev. 2013 Feb;71(2):110-7. doi: 10.1111/nure.12001. Epub 2013 Jan 2. PMID: 23356638.
- Woo KS, Kwok TC, Celermajer DS. Vegan diet, subnormal vitamin B-12 status and cardiovascular health. Nutrients. 2014;6(8):3259-3273. Published 2014 Aug 19. doi:10.3390/nu6083259
- Lederer AK, Hannibal L, Hettich M, Behringer S, Spiekerkoetter U, Steinborn C, Gründemann C, Zimmermann-Klemd AM, Müller A, Simmet T, Schmiech M, Maul-Pavicic A, Samstag Y, Huber R. Vitamin B12 Status Upon Short-Term Intervention with a Vegan Diet-A Randomized Controlled Trial in Healthy Participants. Nutrients. 2019 Nov 18;11(11):2815. doi: 10.3390/nu11112815. PMID: 31752105; PMCID: PMC6893687.
- Gao X, Wilde PE, Lichtenstein AH, Tucker KL. Meeting adequate intake for dietary calcium without dairy foods in adolescents aged 9 to 18 years (National Health and Nutrition Examination Survey 2001-2002). J Am Diet Assoc. 2006 Nov;106(11):1759-65. doi: 10.1016/j.jada.2006.08.019. PMID: 17081826.
- Hodges JK, Cao S, Cladis DP, Weaver CM. Lactose Intolerance and Bone Health: The Challenge of Ensuring Adequate Calcium Intake. Nutrients. 2019;11(4):718. Published 2019 Mar 28. doi:10.3390/nu11040718
- Rozenberg S, Body JJ, Bruyère O, et al. Effects of Dairy Products Consumption on Health: Benefits and Beliefs--A Commentary from the Belgian Bone Club and the European Society for Clinical and Economic Aspects of Osteoporosis, Osteoarthritis and Musculoskeletal Diseases. Calcif Tissue Int. 2016;98(1):1-17. doi:10.1007/s00223-015-0062-x
- Arvidsson B, Ekenved G, Rybo G, Sölvell L. Iron prophylaxis in menorrhagia. Acta Obstet Gynecol Scand. 1981;60(2):157-60. PMID: 7246080.
- Mishra V, Verneker R, Gandhi K, Choudhary S, Lamba S. Iron Deficiency Anemia with Menorrhagia: Ferric Carboxymaltose a Safer Alternative to Blood Transfusion. J Midlife Health. 2018;9(2):92-96. doi:10.4103/jmh.JMH_121_17
- Mansour D, Hofmann A, Gemzell-Danielsson K. A Review of Clinical Guidelines on the Management of Iron Deficiency and Iron-Deficiency Anemia in Women with Heavy Menstrual Bleeding. Adv Ther. 2021 Jan;38(1):201-225. doi: 10.1007/s12325-020-01564-y. Epub 2020 Nov 27. PMID: 33247314; PMCID: PMC7695235.
- Fischer A, Schmelzer C, Rimbach G, Niklowitz P, Menke T, Döring F. Association between genetic variants in the Coenzyme Q10 metabolism and Coenzyme Q10 status in humans. BMC Res Notes. 2011;4:245. Published 2011 Jul 21. doi:10.1186/1756-0500-4-245
- Freriksen JJ, Salomon J, Roelofs HM, et al. Genetic polymorphism 609C>T in NAD(P)H:quinone oxidoreductase 1 enhances the risk of proximal colon cancer. J Hum Genet. 2014;59(7):381‐386. doi:10.1038/jhg.2014.38
- Yu H, Liu H, Wang LE, Wei Q. A functional NQO1 609C>T polymorphism and risk of gastrointestinal cancers: a meta-analysis. PLoS One. 2012;7(1):e30566. doi:10.1371/journal.pone.0030566
- Yadav U, Kumar P, Rai V. "NQO1 Gene C609T Polymorphism (dbSNP: rs1800566) and Digestive Tract Cancer Risk: A Meta-Analysis.". Nutr Cancer. 2018;70(4):557‐568. doi:10.1080/01635581.2018.1460674
- Ding R, Lin S, Chen D. Association of NQO1 rs1800566 polymorphism and the risk of colorectal cancer: a meta-analysis. Int J Colorectal Dis. 2012;27(7):885‐892. doi:10.1007/s00384-011-1396-0
- Palomba S, Orio F Jr, Russo T, et al. BsmI vitamin D receptor genotypes influence the efficacy of antiresorptive treatments in postmenopausal osteoporotic women. A 1-year multicenter, randomized and controlled trial. Osteoporos Int. 2005;16(8):943‐952. doi:10.1007/s00198-004-1800-5
- Jia F, Sun RF, Li QH, et al. Vitamin D receptor BsmI polymorphism and osteoporosis risk: a meta-analysis from 26 studies. Genet Test Mol Biomarkers. 2013;17(1):30‐34. doi:10.1089/gtmb.2012.0267
- Palomba S, Numis FG, Mossetti G, et al. Raloxifene administration in post-menopausal women with osteoporosis: effect of different BsmI vitamin D receptor genotypes. Hum Reprod. 2003;18(1):192‐198. doi:10.1093/humrep/deg031
- Creatsa M, Pliatsika P, Kaparos G, et al. The effect of vitamin D receptor BsmI genotype on the response to osteoporosis treatment in postmenopausal women: a pilot study. J Obstet Gynaecol Res. 2011;37(10):1415‐1422. doi:10.1111/j.1447-0756.2011.01557.
- Mossetti G, Gennari L, Rendina D, et al. Vitamin D receptor gene polymorphisms predict acquired resistance to clodronate treatment in patients with Paget's disease of bone. Calcif Tissue Int. 2008;83(6):414‐424. doi:10.1007/s00223-008-9193-7.