What is the Numex Test
Health assessment questionnaires are widely updated by doctors, nutritionists and other healthcare professionals for estimating people’s health condition, quality of lifestyle and diet (1). Health assessment questionnaires are also used in order to examine habits, eating patterns and lifestyle factors that modulate public health in broader terms (2-5).
The Numex questionnaire was developed by the European Institute of Nutritional Medicine (E.I.Nu.M.) as a tool to examine people’s health condition and to guide them on how to improve their diet and lifestyle, according to current integrated nutritional approaches.
The Numex questionnaire includes questions about habits, symptoms, lifestyle, diet and epigenetic factors such as stress perception, sleep and autonomic nervous system response data in order to examine seven main areas: nutrient intake, oxidative stress, consumption of simple sugars, inflammation, function of the gastrointestinal tract, protein intake and perceived stress (6-14).
The results obtained through the Numex test are intended to provide personalized guidelines for a healthier lifestyle and food choices as unprocessed whole foods, proper hydration and physical exercise, together with the daily intake of essential micronutrients that will provide the recommended daily amount of vitamins and minerals (15,16).
How the Numex Test was created
E.I.Nu.M. developed the Numex Test by analysing and studying the data collected in a study of more than 25 years.
It is necessary to briefly introduce the science of Metabolomics to better understand the scientific bases on which the Numex test was created. Harvard Medicine School considers Metabolomics as the best science to study and measure the products of the chemical reactions (metabolites) that take place in our body (17). Metabolomic analyses (clinical analyses of patients’ metabolomic profiles) can be used at a clinical level to deduce the complete biochemical picture of the state of health and therefore it is possible to identify which nutritional deficiencies may have caused and / or contributed to the development of a disease or ailment.
These particular analyses allow you to diagnose metabolic diseases and identify associated nutritional deficiencies.
It was possible to identify what are the nutritional deficiencies found in most people by studying and comparing the metabolomic analyses of thousands of patients and thanks to the scientific references already published. Thanks to a careful study it was therefore possible to divide these deficiencies into 7 main categories extrapolated from the Metabolome (see graph below), the same categories into which the Numex Test was divided.
The reliability of the Numex Test
The data collected thanks to the metabolomic analyses, which are continuously updated, have been processed to develop the Numex Test, as a tool that can give information on people’s health condition and suggestions on behaviours that could improve it.
The reliability of the test is subject to continuous checks by E.I.Nu.M. The comparison of the results of the metabolomic analyses with the result of the test performed by the same people gave a reliability index of 80%, as can be seen from the graph below. Numex therefore identified the condition of the most important nutritional areas detected by the analyses with great efficiency:
The validation process for the Numex Test is underway.
1. Gibson RS. Principles of nutritional assessment. 2nd edition. Oxford University Press: NY, USA. p. 908. (2005)
2. Kroke A, Klipstein-Grobusch K, Voss S, Möseneder J, Thielecke F, Noack R, Boeing H. Validation of a self-administered food-frequency questionnaire administered in the European Prospective Investigation into Cancer and Nutrition (EPIC) Study: comparison of energy, protein, and macronutrient intakes estimated with the doubly labeled water, urinary nitrogen, and repeated 24-h dietary recall methods. Am J Clin Nutr. Oct;70(4):439-47 (1999)
3. Demosthenes B. Panagiotakos, Natalia Tzima, Christos Pitsavos, Christina Chrysohoou, Emilia Papakonstantinou, Antonis Zampelas, and Christodoulos Stefanadis The Relationship between Dietary Habits, Blood Glucose and Insulin Levels among People without Cardiovascular Disease and Type 2 Diabetes; The ATTICA Study Rev Diabet Stud. Winter; 2(4): 208–215. (2005)
4. Angela D. Liese, Kristina E. Weis, Mandy Schulz, and Janet A. Tooze Food Intake Patterns Associated With Incident Type 2 Diabetes; The Insulin Resistance Atherosclerosis Study Diabetes Care. Feb; 32(2): 263–268. (2009)
5. Lee C, Liese A, Wagenknecht L, Lorenzo C, Haffner S, Hanley A Fish consumption, insulin sensitivity and beta-cell function in the Insulin Resistance Atherosclerosis Study (IRAS) Nutr Metab Cardiovasc Dis. Sep; 23(9): 829–835. (2013) https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3485446/
6. Jyrki K. Virtanen,Rashid Giniatullin, Pekka Mäntyselkä, Sari Voutilainen, Tarja Nurmi, Jaakko Mursu, Jussi Kauhanen & Tomi-Pekka Tuomainen Low serum 25-hydroxyvitamin D is associated with higher risk of frequent headache in middle-aged and older men Scientific Reports volume 7 (2017)
7. Guro F. GiskeødegårdSarah K. DaviesVictoria L. Revell Hector Keun Debra J. Skene Diurnal rhythms in the human urine metabolome during sleep and total sleep deprivation Scientific Reports volume 5 (2015)
8. Vilma Aho Hanna M. Ollila, (…), Tarja Porkka-Heiskanen Prolonged sleep restriction induces changes in pathways involved in cholesterol metabolism and inflammatory responses Scientific Reports volume 6 (2016)
9. Sarah J. Spencer, Aniko Korosi, Sophie Layé, Barbara Shukitt-Hale and Ruth M. Barrientos Food for thought: how nutrition impacts cognition and emotion npj Science of Food volume 1 (2017)
10. Richard P. Bazinet & Sophie Layé Polyunsaturated fatty acids and their metabolites in brain function and disease Nature Reviews Neuroscience volume 15, pp 771–785 (2014)
11. Parth J. Parekh, MD1, Luis A. Balart, MD, MACG1 and David A. Johnson The Influence of the Gut Microbiome on Obesity, Metabolic Syndrome and Gastrointestinal Disease Clinical and Translational Gastroenterology 6 (2015)
12. Tom Van de Wiele, Jens T. Van Praet, Massimo Marzorati, Michael B. Drennan & Dirk Elewaut How the microbiota shapes rheumatic diseases Nature Reviews Rheumatology volume 12, pp (2016)
13. L Kinsey, & S Burden A survey of people with inflammatory bowel disease to investigate their views of food and nutritional issues European Journal of Clinical Nutrition volume 70, pp (2016) https://www.nature.com/articles/ejcn201657
14. J E Löfvenborg, T Andersson, P-O Carlsson, M Dorkhan, L Groop, M Martinell, T Tuomi, A Wolk & S Carlsson Fatty fish consumption and risk of latent autoimmune diabetes in adults Nutrition & Diabetes volume4, pp (2014)
15. “Healthy Eating Plate & Healthy Eating Pyramid”. Harvard University, TH Chan School of Public Health, Boston. 2017. https://www.hsph.harvard.edu/nutritionsource/healthy-eating-plate/
16. Dickinson A. The Benefits of Nutritional Supplements, 4th edition, Council for Responsible Nutrition Washington D.C. (2012) https://www.crnusa.org/resources/benefits-nutritional-supplements
17.Shaw J.Fathoming Metabolism.The study of metabolites does an end run around genomics to provide telling clues to your future health. Harvard Magazine, May-June 2011 https://www.harvardmagazine.com/2011/05/fathoming-metabolism?page=all