Food composition data and food composition databases

Early food composition studies were carried out to identify and determine the chemical nature of the principles in foods that affect human health. These studies were also concerned with the mechanisms whereby chemical constituents exert their influence and provided the basis for the early development of the science of nutrition (McCollum, 1957), and they continue to be central to the development of the nutritional sciences. Current knowledge of nutrition is still incomplete, and studies are still required, often at an ever-increasing level of sophistication, into the composition of foods and the role of these components and their interactions in health and disease.

Somogyi (1974) reproduced a page of the earliest known food composition table, dated 1818. Ever since, it has been customary to record food composition data in printed tables for use by both specialists and non-specialists. While printed tables will continue to be produced, computerized data systems have replaced them in some settings because of the ease with which data can be stored, and the facility with which the large amounts of data can be accessed and processed.

These systems are increasingly used to generate printed and computerized food composition tables and data files. Computerized and printed tables generally contain a subset of nutrients and foods and often no further documentation. A single computerized data system can generate a variety of tables and files, each containing specific subsets of numeric, descriptive and graphical information. Examples are the different user databases released by New Zealand (Burlingame, 1996).

Studies of the relationship between diet and health have led to increased interest in the range of biologically active constituents present in foods that accompany the nutrients, and data for these constituents are often required, as are data for additives and contaminants. A well-designed data system can accommodate non-nutrient data, although this should not detract from the primary objective of the database programme – the provision of data on the nutrient content of foods.

Methods of compiling food composition databases

Early food composition tables were based on analyses carried out in the laboratories of researchers such as Von Voit in Germany, Atwater in the United States of America and Plimmer in the United Kingdom (UK) (Somogyi, 1974; Atwater and Woods, 1896; Widdowson, 1974). Later, the United States moved towards compiling tables from scrutinized data produced by a number of laboratories. An element of this procedure was introduced into the UK tables, where the third edition of McCance and Widdowson (1940) included vitamin and amino acid values drawn from the literature. Southgate (1974) distinguished these two methods as the direct and indirect method of compiling tables. These methods, and other procedures for compiling food composition data, were described by INFOODS (Rand et al., 1991).

Direct method

The advantage of the direct method, in which all of the values are the results of analyses carried out specifically for the database being compiled, is that close control of the sampling, analysis and quality control procedures yields highly reliable data. Early UK food composition workers analysed different purchases of the same food separately, but without duplicate determinations, with the intention of gaining some limited information on nutrient variation in each food (McCance and Shipp, 1933). In subsequent versions of the UK tables, however, the various purchases of the food were combined, reducing costs and increasing the number of foods that could be analysed in a given period of time (McCance, Widdowson and Shackleton, 1936). Even with this procedure, the direct method remains costly and time-consuming, and imposes pressure on the analytical resources available in many parts of the world.

Indirect method

The indirect method uses data taken from published literature or unpublished laboratory reports. There is consequently less control over the quality of the data, which may be uneven. Great care must therefore be taken in their appraisal for inclusion in the database. In some cases, values are imputed, calculated (see below), or taken from other tables or databases, and it may be impossible to refer back to the original source; these values carry a lower degree of confidence. The indirect method is most commonly employed when analytical resources are limited, or the food supply is largely drawn from food imported from other countries where compositional data are available. Although the indirect method is clearly less demanding of analytical resources than the direct method, the level of scrutiny required often makes it time-consuming and costly.

Combination method

Most food composition databases nowadays are prepared by a combination of the direct and indirect methods, containing original analytical values together with values taken from the literature and from other databases as well as imputed and calculated values. This combination method is the most cost-effective and is particularly successful when staple foods are analysed directly, and data for less important foods are taken from the literature (including that from other countries, if necessary). However, minimization of the amount of imputed and calculated values in principle increases the reliability and representativeness of the database.

Types of food composition data

Food composition databases currently available contain compositional values of differing quality, reflecting the different ways in which they were obtained. If data are to be used internationally they must be of consistent and compatible quality so that they can be used in combination for collaboration between individuals and countries in nutritional research, nutrition education, food regulation, and food production and processing. Data types and sources can be identified in food composition databases by codes (USDA, 2003a; Burlingame et al., 1995a), as is done in many countries, and by reference (Wu Leung, Butrum and Cheng, 1972). In general order of preference, the sources of data are:

Original analytical values

These are values taken from the published literature or unpublished laboratory reports, whether or not they were from analyses carried out explicitly for the purpose of compiling the database. They may be assimilated into the database unmodified, or as a selection or average of analytical values, or as combinations weighted to ensure that the final values are representative. Original calculated values are included in this category (e.g. protein values calculated by multiplying the nitrogen content by the appropriate factor, or fatty acids per 100 g food calculated from fatty acid values per 100 g total fatty acids).

Imputed values

These data are estimates derived from analytical values obtained for a similar food (e.g. values for peas used for green beans) or for another form of the same food (e.g. values for “boiled” used for “steamed”). They may also be derived by calculation from incomplete or partial analyses of a food (e.g. carbohydrate or moisture by difference, sodium derived from chloride values or, more commonly, chloride calculated from the value for sodium). Similar calculations can be made by comparing data for different forms of the same food (e.g. “dried” versus “fresh” or “defatted” versus “fresh”).

Calculated values

These are values derived from recipes, calculated from the nutrient contents of the ingredients and corrected for preparation factors: loss or gain in weight, usually referred to as yields, and micronutrient changes, usually referred to as retention factors. Such values are only rough estimates, because the preparation conditions for recipes vary dramatically, such as cooking temperature and duration, which will significantly affect yield and retention. Another calculation method is the calculation of the nutrient values of cooked foods based on those of raw foods or foods cooked in a different way, using specific algorithms, retention and yield factors.

Borrowed values

These are values taken from other tables and databases where reference back to the original source may or may not be possible. Adequate reference to original sources is necessary to justify a borrowed value. In some cases, the borrowed values should be adapted to the different water and/or fat contents.

Presumed values

These are values presumed as being at a certain level or as zero, according to regulations.

Sources of food composition data

Foods are chemically analysed for a variety of purposes. Food composition databases rely on nutritional and toxicological analyses conducted by government, academia and industry to determine the potential contributions of foods to the diet, and to determine compliance with regulations concerning composition, quality, safety and labelling. Foods may also be analysed for the purpose of ongoing monitoring of the food supply (e.g. Bilde and Leth, 1990). All of these compositional studies produce data that can be considered for entry into a food composition database.

Nutritional evaluation of foods

In human nutrition studies, the composition of foods is investigated, ideally, in a research setting interacting with one or more other areas of nutrition research (Figure 1.1). The data are most useful when they represent foods in the forms generally consumed (see Chapter 5, Sampling).

In agriculture, factors such as disease resistance and yield, rather than nutritional value, have tended to dominate decision-making regarding policies and programmes. Similarly, in food technology economic considerations such as consumer appeal and profitability have been the major influences on product development. Attitudes are changing, however, and nutritional quality is now one of the factors considered in cultivar selection and the development of processed foods.

The production, handling, processing and preparation of foods profoundly affect their nutritional quality. Extensive literature covers agricultural practices (climate, geochemistry, husbandry, post-harvest treatments); processing methods (freezing, canning, drying, extrusion); and stages in food preparation (holding, cutting, cooking). Most nutritional studies in these areas, however, cover a limited range of nutrients (notably labile vitamins); very little information is provided on the broad range of nutrients (Henry and Chapman, 2002; Harris and Karmas, 1988; Bender, 1978; Rechigl, 1982). Nevertheless, data from these types of studies can often be useful in food composition databases, either as data per se, or in establishing relevant yield and retention factors for calculations (see Chapter 9).

Food regulations

Levels of certain nutrients, additives and contaminants in foods are monitored for several reasons. Some nutrients, for example, may react adversely under particular processing conditions, producing poor sensory quality or affecting the safety of the food (e.g. trans fatty acids). Labelling regulations also require prescribed levels of nutrients in specific foods (e.g. vitamins and minerals in fortified foods, polyunsaturated fat levels in margarine). Certain toxic substances are limited to prescribed levels and are monitored by government, industry and other laboratories. The nutrient content of manufactured foods is rarely made available in electronic format to compilers, and care must be exercised when compiling databases using information provided on food labels.

Simplified food composition database or tables

Simplified databases or tables can be produced from the main user database. In these, fewer nutrients are covered, and some reductions of food categories may be possible (e.g. for meat cuts data may appear only for “medium cooked,” omitting “rare” and “well cooked”). Values can appear as units per 100 g of food or per average serving, expressed in household units or portion sizes. Modified versions of the database can also be produced to assist manufacturers in food labelling. Various types of database or printed table can be produced from the same comprehensive database, ranging from a fairly extensive version for the professional user to a smaller version for consumers or for users involved in large-scale food preparation.

Special-purpose food composition tables and databases

Tables and databases restricted to selected nutrients can be produced for people with special dietary needs or interests (e.g. for diabetics, or for people with kidney disorders for whom a diet controlling protein, sodium and potassium is required, or for nutrition educators, or for people wishing to lose weight). Data may be presented per 100 g of food, or per portion size or common household measures. Such tables and databases might be produced showing foods with ranges of nutrients – high, medium and low levels, for example. Data could also be given in other useful units (e.g. sodium and potassium in millimoles for renal patients).

Types of food composition database programme

National

Ideally, each country should have an established programme to manage its own food composition data, the data being considered an important national resource, as important as any other national collection of data.

While the level of certain nutrients in some foodstuffs will vary little between countries (e.g. the amino acid composition of lean meats), other nutrients, even in foods that are available worldwide, will vary greatly because of differing cultivars, soils, climates and agricultural practices. Recipes for composite dishes with the same name vary between countries. Different technological practices are also used; flour, for example, is produced and used at different extraction rates and may be fortified to different levels with different nutrients (Greenfield and Wills, 1979). Some countries have unique foods, food products or processing procedures (Somogyi, 1974). For these and other reasons, it is essential to develop a national food composition database programme, and to ensure that such a programme draws on data from other countries only when those values are considered applicable to nationally consumed foods.

Although attempts are being made to develop common food standards (e.g. the Joint FAO–World Health Organization [FAO/WHO] Food Standards Programme, Codex Alimentarius (FAO/WHO, 2003a,b), differences in food descriptions will continue to occur between countries.

Regional

The preparation of regional food composition databases is of great importance. Many countries, particularly in the developing world, lack the resources needed for a full-scale national food composition programme, but share a similar food supply to that of neighbouring countries. Cooperation between United States government departments, the Institute of Nutrition of Central America and Panama (INCAP) and FAO has produced some early regional food composition tables for Latin America (Wu Leung and Flores, 1961), Africa (Wu Leung, Busson and Jardin, 1968), East Asia (Wu Leung, Butrum and Cheng, 1972) and the Near East (FAO, 1982). More recently, this cooperation with FAO/UNU/INFOODS has led to the publication of regional tables for Pacific island countries (Dignan et al., 1994), Latin America (LATINFOODS, 2000) and Southeast Asia (Puwastien et al., 2000).

Some countries are collaborating on food composition analyses among themselves – for example, those in the North European region and those in the South Pacific region (Becker, 2002; South Pacific Commission, 1982). Other regional programmes may be those serving participating countries in multicountry epidemiological studies (Slimani et al., 2000). Simplified national programmes can be derived from such international or regional programmes.

Criteria for a comprehensive food composition database

The current high level of interest in nutrition requires that food composition databases meet the following criteria:

1. Data should be representative

Values should represent the best available estimate of the usual composition of foods in the forms most commonly obtained or consumed. Ideally, some measure of variability in the composition of the food should be given.

2. Data should be of sound analytical quality

Original analytical data from rigorously scrutinized sources are the ideal. Values from other databases, and imputed or calculated data should be included only when original analytical data are not available or are known not to be of sufficient quality. High-quality analytical data are those produced by methods that have been shown to be reliable and appropriate to the food matrix and nutrient in question. These methods must be applied proficiently, and evidence of this proficiency is required to assure data quality. It is also desirable that the analyst and the laboratory satisfy criteria of good laboratory practice. Further, evidence is required to show that the food sample was representative and was collected and handled properly. However, for existing data, documentation on sampling, source or analytical method is often not available, at least electronically.

Chapters 5, 6, 7 and 8 contain more specific guidelines for sampling procedures, methods of analysis and assurance of data quality; these three areas should always be considered in determining the quality of analytical food composition data.

3. Coverage of foods should be comprehensive

The database should include all foods that form a major part of the food supply and as many as possible of the less frequently consumed foods. The selection of foods for inclusion in a database is discussed in Chapter 3.

4. Coverage of nutrients should be comprehensive

Values should be included for all of the nutrients and other components known or believed to be important to human health. National priorities regarding health will have a major role in deciding which nutrients should be included. The criteria for selecting nutrients to be covered are discussed in Chapter 4.

5. Food descriptions should be clear

To be easily identified, foods must be unambiguously named and described. (Food nomenclature is discussed by McCann et al. [1988]; Truswell et al. [1991]; Møller and Ireland [2000a,b]; and Unwin and Møller [2003].)

6. Data should be consistently and unambiguously expressed

The data should be unambiguous in mode of expression and consistent in the use of units, factors used in calculation, and procedures used in rounding values.

7. Origins of data should be provided at nutrient value level

Information should be given on the sources of the data, noting whether data are analytical, calculated or imputed, and, as appropriate, on the procedures of any calculation and imputation, and the methods of sampling and analysis. Confidence or quality codes for the values should also be supplied.

8. Tables and databases should be easy to use

In addition to having clear terminology and systematic expression, databases and computerized tables must be easily accessible and readily understood. Printed tables should be of clear legibility and manageable size and weight.

9. The content of different databases should be compatible

The descriptions of foods, modes of expression and derivations of values should conform as closely as possible to existing international standards (e.g. the INFOODS tagnames) and to other major comprehensive food composition databases. Scientific needs require computerized databases and tables to be constructed with a view to using them in combination with other such systems.

10. Database should have few missing data

It follows from the above that any food composition database or table should aim to have as few gaps as possible because missing data can significantly distort the resultant nutrient intake estimations. It may be better to include imputed or borrowed data, always clearly identified as such, than no data at all. On the other hand, practical considerations often dictate that an incomplete database or table be produced to meet immediate needs. Information besides nutrient data (e.g. data on toxic substances or additives), though useful, is not essential at this stage.

Uses of food composition data

Food composition data are used primarily for the assessment and the planning of human energy and nutrient intakes. In both cases, the approach is most useful when applied to groups rather than individuals. Assessment and planning can be divided into several subcategories for which the precise requirements of the database differ and for which additional information is required.

Assessment of nutrient intakes (nutritional analysis)

When the weights of consumed foods are known, food composition data permit the intake of each nutrient to be calculated by multiplying the weight of each food by the concentration of the nutrient in that food and then adding the results, according to the equation:

I =Σ (W₁C₁ + W₂C₂ + W₃C₃ + ........W_nC_n)

where: I = intake of the nutrient, W₁ = weight consumed of food 1, C₁ = concentration of the nutrient in food 1, etc.

Knowledge of nutrient intakes is required at several levels, as outlined below.

Individual level

A person's nutrient intake can be calculated by the use of food composition data and food intake data (estimated from a dietary history or dietary recall or measured in a weighed intake study) (Cameron and van Staveren, 1988; Nelson, 2000). This information can show gross dietary adequacy or inadequacy, or dietary imbalance, and is important in the determination of dietary advice or in prescription of a therapeutic diet. The user must be aware, however, that due to the natural variability of foodstuffs, food composition data may not predict the composition of a single portion of any particular food with accuracy.

Group level

Foods consumed by populations can be measured by various techniques (Marr, 1971) and translated, by means of food composition data, into nutrients consumed. The results give one indication of the nutritional status of the group (Jelliffe and Jelliffe, 1989; Gibson, 1990) and may be used to explore the relationship of a diet to a variety of health indices – sickness and death patterns, growth rate, birth weight, measures of clinical nutritional status, physical performance, etc. Examples of groups usually studied in this way are:

physiological groups, such as growing children, pregnant and lactating women, elderly people;
socio-economic groups (e.g. racial, caste, income or occupational);
clinical groups, such as patients and healthy controls;
intervention groups, usually drawn from the preceding categories, which receive a dietary supplement or other programmes;
cohorts in epidemiological studies of diet and health (Riboli and Kaaks, 1997).

Data drawn from studies of groups are used not only for identification of nutritional problems and planning of nutrition interventions to counteract them; they can also be employed in research that seeks to identify nutrient intakes desirable for good health. The results of such studies may feed back into food and nutrition policy in the form of food supplement programmes for children, food stamps for low-income groups, dietary advice to pregnant women, preventive diets for reducing heart disease rates, etc.

National and international levels

National statistics for agricultural production, adjusted for exports, imports, non-food use and gross wastage, are multiplied by nutrient composition data and divided by the total population to produce estimates of gross nutrient availability per capita. These data permit an assessment of the gross adequacy or inadequacy of the national food supply and indicate shortfalls or excesses. Food monitoring systems (e.g. Bilde and Leth, 1990) can follow the consumption of desirable and undesirable substances over a period of years.

Data from individual nations can be assembled to give cross-national or worldwide pictures of food and nutrient availability; such data are used in formulating food and nutrition policy, in setting goals for agricultural production, in formulating guidelines for consumption and particular policies such as food fortification or food supplementation (Buss, 1981).

Internationally, this information has implications for trade and for the development of assistance policies. In research, comparisons of nutrient intakes of different countries, together with other epidemiological data, enable further elucidation of the role of dietary constituents in health and disease. At present, long-term changes in the food supply can only be monitored adequately by the use of up-to-date food composition tables and databases. For example, the fat and iron content of meat have been altered in Western countries by changes in methods of husbandry and butchering. Comparison of today's cuts with those of ten years ago can be made by reference to past food composition tables (Vanderveen and Pennington, 1983).

Subnational and community levels

Similar calculations can be made to provide estimates of the distribution of nutrients within a country. These findings can indicate actual or potential nutritional problems. Such studies are often critically important for developing countries that have diverse geographical regions. Periodic surveys, as part of a full system of nutritional surveillance, can monitor nutritional change and the effectiveness of food and nutrition policies.

Planning, advising or prescribing food and nutrient intakes (nutritional synthesis)

The physiological requirements or recommended intakes of most nutrients have been estimated (e.g. FAO/WHO/UNU, 1985), and it is the job of the nutritionist to translate these requirements or recommendations into desirable food intakes, at varying levels of cost. Again, this task can be performed at several levels, as outlined below.

Prescription of therapeutic diets

A therapeutic diet must be nutritionally balanced and adequate while at the same time controlling the intake of one or more specified nutrients. The prescription of therapeutic diets, therefore, requires professional training and a detailed understanding of the composition of foods. Table 1.2 lists types of disorder that require therapeutic diets, together with the dietary components that must be controlled. Unfortunately, most available food composition tables and databases do not hold information on all of the components listed in Table 1.2, and primary data sources may have to be consulted to obtain the required information.

Planning of institutional diets

Food composition data are used to translate recommended nutrient intakes into cost-limited foods and menus. Large sectors of the population (e.g. military establishments, workplace cafeterias, hospitals, prisons, schools, day-care centres and hotels) are provided with meals in this way.

Table 1.2 Examples of clinical conditions that require food composition information for the planning of therapeutic diets
Clinical condition	Composition information required
Requiring general dietary control
Diabetes mellitus	Energy value, available carbohydrate, fat, protein, dietary fibre
Obesity	Energy value, fat
Hypertension	Energy value, sodium, potassium, protein
Renal disease	Protein, sodium, potassium
Deficiency states
Anaemia	Iron, folate, vitamin B12
Vitamin deficiencies	Specific vitamin contents
Metabolic disorders
Haemochromatosis	Iron
Hyperlipidaemias	Fat, fatty acids, cholesterol
Inborn errors of amino acid metabolism	Amino acids
Gout, xanthinuria	Purines
Gall bladder disease	Fat, calcium, cholesterol, dietary fibre
Wilson's disease	Copper
Intolerances
Disaccharides, monosaccharides	Individual sugars, especially sucrose, lactose, fructose, galactose
Gluten (and other specific proteins)	Gluten, specific proteins
Migraine	Monoamines
Allergies	Specific proteins
Note:This list is not intended to be inclusive.

National food and nutrition policy

A national food and nutrition policy will often define goals for the intake of certain nutrients. These goals must be translated into food production targets for the agriculture sector or into food consumption targets for the market or the public health sector (e.g. through increased subsidy or promotion of certain foods).

Nutritional regulation of the food supply

Food regulators use nutritional data on primary foods or “traditional” food products as a reference point for desirable nutrient levels for processed and newly introduced foods. For example, consumers should be able to rely on a traditional dairy product having certain levels of calcium and riboflavin; new processing techniques should not significantly alter the essential nutritional quality of the well-recognized product. Similarly, a manufactured or fabricated substitute should provide the same nutritional value as the food it is intended to replace (Vanderveen and Pennington, 1983).

A food composition database can also provide a preliminary check on label information or claims. For example, a food may be advertised as high in nutrient X, and information on the composition of its listed ingredients will indicate whether that food product could be high in nutrient X without fortification (for which special regulations may exist). Further, data on “new” cultivars being evaluated for widespread commercial introduction can be compared with data for traditional cultivars.

Some countries permit the nutrition data used in labelling certain composite foods to be calculated from nutrient data for ingredients taken from food composition tables and databases. In such cases, it must be ensured that nutrient values from the food composition tables and databases are comparable with those of the food regulations concerning food labelling.

Planning of nutrition intervention programmes

Nutrition interventions, such as food aid programmes, supplementation schemes and disease prevention programmes, require the use of food composition data in order to translate specific nutrient needs into food requirements. Note that such programmes may require confirmation by direct analysis, particularly at the research level.

Limitations of food composition databases

The limitations of food composition tables or databases are often not sufficiently understood by many users. Foods, being biological materials, exhibit variations in composition; therefore a database cannot accurately predict the composition of any given single sample of a food. Hence, although food composition tables and databases can be used to devise a diet, meal or supplement, the levels of nutrients are essentially estimates. For metabolic studies a direct analysis is usually necessary to obtain the required accuracy in the measured intake of the nutrients being studied.

Further, food composition databases and tables are limited in their usefulness for regulatory as well as scientific purposes. They cannot predict accurately the nutrient levels in any food; this is especially true for labile nutrients (e.g. vitamin C and folates) or constituents added or removed during food preparation (fat, moisture). Furthermore, the composition of a given food may change with time (e.g. a manufacturer's formulation may change) invalidating the use of the values in the database. Predictive accuracy is also constrained by the ways in which data are maintained in a database (as averages, for example).

Food composition databases frequently cannot be used as literature sources for comparison with values obtained for the food elsewhere. Values from one country should be compared with values obtained in other countries by reference to the original literature. Food composition databases can be used more confidently when the values are known to be based on original analytical values. Any imputations, calculations, weightings or averaging must be clearly documented and, most important, food items must be adequately described to enable comparisons to be made.

It seems that, despite major efforts during the past 20 years on harmonizing food descriptions, nutrient terminology, analytical methods, calculation and compilation methods, values from existing food composition tables and databases are not readily comparable across countries. In addition, users may not always be aware of the difference in nutrient values between raw and cooked foods and might erroneously use the values for raw foods in place of those for cooked ones. This is often the case in countries using food composition tables that contain mainly raw foods.

Finally, there has been an increase in the consumption of manufactured foods and mineral and vitamin supplements, accounting for up to 60 percent of the total food intake, but these are rarely listed in food composition tables and databases (Charrondiere et al., 2002). As a result, it can be assumed that nutrient intake estimations are increasingly unrepresentative of the actual nutrient intake.

Users

The users of food composition tables and databases vary greatly: economists, agricultural planners, nutritionists, dietitians, food service managers, food and agricultural scientists, manufacturers, food technologists, home economists, teachers, epidemiologists, physicians, dentists, public health scientists, non-specialist consumers and journalists. Access to different types of computerized tables and databases is required to suit these differing needs; this is now achievable due to the availability of computers.

Food Composition Tables by Sama chifen