• Food composition data

    Food composition data

    • Food composition data (FCD) are detailed sets of information on the nutritionally important components of foods and provide values for energy and nutrients including protein, carbohydrates, fat, vitamins and minerals and for other important food components such as fibre. The data are presented in food composition databases (FCDBs).

      In the UK, FCD is listed in tables known as The Chemical Composition of Foods, McCance and Widdowson (1940) and in the first edition the authors stated that:

      ‘A knowledge of the chemical composition of foods is the first essential in the dietary treatment of disease or in any quantitative study of human nutrition’.

      This demonstrates the main reason for establishing FCD at that time. To this day, food composition studies remain central to nutrition research into the role of food components and their interactions in health and disease. However, due to increasing levels of sophistication and complexity in nutrition science, there is a greater demand for complete, current and reliable FCD, together with information on a wider range of food components, including bioactive compounds.

      FCD are important in many fields including clinical practice, research, nutrition policy, public health and education, and the food manufacturing industry and is used in a variety of ways including: national programmes for the assessment of diet and nutritional status at a population level (e.g. epidemiological researchers assessing diets at a population level); development of therapeutic diets (e.g. to treat obesity, diabetes, nutritional deficiencies, food allergy and intolerance) and institutional diets (e.g. schools, hospitals, prisons, day-care centres) and nutrition labelling of processed foods.

      The earliest food composition tables were based solely on chemical analyses of food samples, which were mostly undertaken specifically for the tables. However, as the food supply has evolved, and with the increasing demand for nutritional and related components, it has become more difficult for compilers to rely only on chemical analysis when compiling FCDBs. For example, in the UK the third edition of The Composition of Foods presented data on vitamin content of foods. However, due to the amount of information already available and in order to avoid the need to analyse every food for every vitamin, values from the scientific literature were included, although the tables are still predominately based on analytical data. Nowadays, food composition databases tend to be compiled using a variety of methods, including:

      Chemical analysis of food samples carried out in analytical laboratories is typically the preferred method for creating FCD. The food samples are carefully chosen using a defined sampling plan to ensure that they are representative of the foods being consumed in a country. This includes accounting for factors that could affect the nutrient content of a food as purchased (e.g. region and/or country of origin, season, brand, fortification) or as consumed (e.g. storage, preparation and cooking methods). If necessary, further preparation and cooking takes place prior to the analysis using appropriate analytical methods and often appropriate samples of foods are combined rather than taking averages of individually analysed food samples. Ideally, the methods used for analysis should have been shown to be reliable and reproducible, i.e. those recommended by organisation such as the Association of Official Analytical Chemists (AOAC) or the International Organisation for Standardisation (ISO).

      • Variability in the composition of foods between countries, owing to, for example, season, cultivar or variety, brand, fortification levels
      • Incomplete coverage of foods or nutrients leading to missing values
      • Age of data (limited resources mean that, inevitably, some values are not current)
      • Chemical analysis of food samples carried out in analytical laboratories
      • Imputing and calculating values from data already within the dataset
      • Estimating values from other sources, including manufacturers food labels, scientific literature and FCDBs from other countries.
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    • Food composition data