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Technical Notes on Nutrient Data

Energy value (Kcals): Calculated using the conversion factors: protein 4 kcal/g, fat 9 kcal/g, carbohydrate 4kcal/g and alcohol 7 kcal/g.

 

Energy value (kJ): Calculated using the conversion factors: protein 17kJ/g, fat 37 kJ/g, carbohydrate 17 kJ/g and alcohol 29 kJ/g

 

Amino Acids Fatty acids: Fatty acids are available via the research edition of Nutritics. Fatty acid and amino acid data are not readily available/accessible from manufacturers which would limit the extent to which Nutritics can complete food requests accurately.

 

Starch: Includes dextrins but excludes resistant starch, starch is expressed by weight.

 

Sugars: Sugars include free monosaccharides and disaccharides. In cereals the contribution from glucofructans is also included. The value does not include any contribution from oligosaccharides which are provided separately. Note that the breakdown of sugar (glucose, fructose components etc) is incomplete in the databases, and therefore should be considered for indicative purposes only. These values are hidden in the report by default and are expressed by weight.

 

Free Sugars: All sugars that have been added by a food manufacturer, cook or consumer to a food and include those sugars naturally found in fruit juice, honey and syrups. They do not include sugars naturally found in milk and milk products, nor in fruit and vegetables.

 

Non-starch polysaccharides (Englyst method) Includes insoluble fibre (cellulose, insoluble non-cellulosic polysaccharides) and soluble fibre (soluble cellulosic polysaccharides). NSP is provided in weight of the actual component and not monosaccharide equivalents.  

 

Total dietary fibre (AOAC method): Includes substances measuring as lignin and also resistant starch by weight.  Fibre by the AOAC method is not included in the UK food tables, but has been added to Nutritics from other sources.

 

Glycemic Index: GI data is from the International table of glycemic index and glycemic load values and the University of Sydney (Human Nutrition Unit) GI database, or imputed from similar foods if no data is available. The reference food used is glucose (GI=100). A GI of 55 or less is considered low, 56-69 is medium and 70+ is considered high. It is important to be aware that GI can vary based on cooking method, duration, ripeness, season, food combination, manufacturing process and many other factors. The GI of meals is automatically calculated and should be considered for indicative purposes only.

 

Glycemic Load: Glycemic load is calculated from the formula (GI*carbohydrate)/100. GL may be is more useful than GI since it accounts for both the GI and the portion size of carbohydrate consumed. (GL = GI * carbohydrate of serving / 100). One GL unit is equivalent to the glycemic effect of consuming 1g of glucose. Interventions targeting weight loss, insulin resistance and the metabolic syndrome appear to benefit from low GL dietary strategies. A meal with a GL of <10 is considered low, 11-19 is medium and >20 is considered high. A daily total GL of <80 is considered low, <120 is medium and >120 is considered high.

 

Additional information sources:

T.R. Fenton, M., Eliasziw, A.W. Lyon, S.C. Tough. D.A. Hanley, “Meta-analysis of the quantity of calcium excretion associated with the net acid excretion of the modern diet under the acid-ash diet hypothesis.” Am J Clin Nutr 88 : 1159–1166, 2008.
L. Frassetto, R. C. Morris, Jr. R.C. Jr., D. E. Sellmeyer, K. Todd, and A. Sebastian, “Diet, evolution and aging—the pathophysiologic effects of the post-agricultural inversion of the potassium-to-sodium and base-to-chloride ratios in the human diet,” European Journal of Nutrition, vol. 40, no. 5, pp, 200–213, 2001 

J.E. Kerstetter, K.O. O'Brien, D.M. Caseria, D.E. Wall, K.L. Insogna  “The impact of dietary protein on calcium absorption and kinetic measures of bone turnover in women”. J Clin Endocrinol Metab 90 : 26–31, 2005 .

 S. T. Reddy, C. Y. Wang, K. Sakhaee, L. Brinkley, and C. Y. Pak, “Effect of low-carbohydrate high-protein diets on acid-base balance, stone-forming propensity, and calcium metabolism,”6 Journal of Environmental and Public Health American Journal of Kidney Diseases, vol. 40, no. 2, pp. 265–274, 2002.

T. Remer and F. Manz, “Estimation of the renal net acid excretion by adults consuming diets containing variable amounts of protein,” American Journal of Clinical Nutrition, vol. 59, no. 6, pp. 1356–1361, 1994

 L.A. Spence, E.R. Lipscomb, J. Cadogan , B. Martin, M.E. Wastney, M. Peacock, C.M. Weaver. “The effect of soy protein and soy isoflavones on calcium metabolism in postmenopausal women”: A randomized crossover study. Am J Clin Nutr 81 : 916–922, 2005. 

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