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Food composition data

There are three important aspects of food composition data themselves: (a) what data exist, (b) how good these data are, and (c) how easy these data are to obtain.

What Food Composition Data Exist?

The number of foods that have been analysed for their content varies tremendously around the world. Tables which include these data are available in a variety of forms
(note that these tables are not entirely independent, since many of the basic data are shared among them):

- international tables (e.g. Platt's Tables of Representative Values of Foods Commonly Used in Tropical Countries);
- regional tables (e.g. FAO and USHEW's Food Composition Tables for Use in Africa);
- national tables (e.g. USDA's Handbook No. 8);
- food industry data bases (many major food companies have their own data bases);
- commercial data bases (there are a large number of diet analysis programs, which include data bases, available for purchase by individual consumers);
- local, special-purpose tables (many hospitals maintain data bases for menu planning and nutrition guidance);
- journal articles (a number of journals, such as the Journal of the American Dietetic Association and Ecology of Food and Nutrition, frequently publish papers containing food composition data).

While there is no complete index to all the food composition data that exist, several partial directories are available. The Food and Agriculture Organization (FAO) of the United Nations published a listing in 1975 which covered international, regional, and national tables [4]. This is now out of date and FAO has no plans for its updating. In 1986 INFOODS issued a similar directory of tables currently used [8]. EUROFOODS (paper 5) and NORFOODS (paper 16) have prepared listings of data available within their regions. Within the United States, Loretta Hoover of the University of Missouri-Columbia annually issues a Nutrient Data Bank Directory, which includes characteristics and contents of currently available data bases [6]. Additionally, Darlene Hildebrandt, of the University of Washington in Seattle, issues a listing of Computer Programs and Databases in the Field of Nutrition [5].

With respect to the data that are available, in North America and Western Europe it is usually possible to find basic nutrient composition data for most common foods. However, there are many regions throughout the world where data on the composition of even the most frequently consumed foods do not seem to be available, or when available are seriously out of date (papers 14 and 15).

Beyond the problem of determining what data exist is the problem of determining what the available data represent. While often an introduction to printed tables will provide some indication of the analytic methods used, rarely is sufficient information given on how the food samples were gathered and analysed, and on how the data themselves were scrutinized and manipulated. Moreover, only infrequently is there any indication of the variability inherent either in the food or in the analytic method.

In terms of the data that are not available to potential users, no food composition data system contains values for all the components or foods desired by all users, and it is unlikely that any table or data base ever will, because of the rapid expansion of the number of foods and nutrients of interest.

Missing Components

The components of foods that are most frequently missing include:

- nutrients (especially trace minerals, some B vitamins, and lipid-soluble vitamins);
- subcomponents of nutrients and classes of nutrients, such as retinoids, carotinoids, fatty acids, starches, specific sugars, etc.;
- non-nutrients such as dietary fibres, xanthines, allergens, toxins, and selected con taminants;
- ingredients including additives.

While the situation is often that there are not good, reliable methods for assaying certain components [10,12], many of the data do not exist simply because of the magnitude of the task of collecting them. Users with specific needs have two options: (a) they can generate the data themselves, gathering representative samples of the foods of interest and assaying them for the desired components, or (b) they can estimate (impute) the missing values from known data on similar foods and components. The first option requires resources that users rarely have available, while the second requires clear and well-defined rules for estimation, rules which do not currently exist. An associated problem is that rarely do data produced by individual users enter into the public store of food composition data, with or without appropriate documentation.

Missing Foods

While data on new, manufactured foods and foods infrequently consumed are often missing from food tables, there is a major and significant gap concerning the composition of "foods as consumed." Many of the data in tables represent foods that are "raw," but many (if not most) foods are eaten after being processed, stored, and/or prepared in various ways that may each affect at least some of the nutrient levels [1]. Moreover, often the data on prepared dishes in the tables are not the results of analyses but have been estimated by the compilers of the tables.

Two important types of "foods as consumed" are mixed dishes, such as stews and curries, and foods that are purchased already prepared, such as those obtained in a restaurant. For these foods, composition data, based on either analysis or estimation, must start from a recipe. However, it is often difficult to define, much less obtain, "standard" or representative recipes for most of these foods. If a recipe can be selected, one must then address the issues of labile or soluble nutrients, cooking losses, nutrient interactions, and fluid or fat loss (or gain) which can significantly alter nutrient concentration per unit weight. Additional problems arise from shifts in the availability and costs of ingredients which frequently lead to modifications of the recipes.

Efforts are proceeding in two general directions with respect to adding data to food tables. First, more analytic methods are being developed and analyses being conducted, and, second, discussions and research are being carried out to develop guidelines for making estimation more accurate. However, both these efforts must be greatly expanded, and co-ordinated, before users can devote their efforts to the using of food composition data rather than to the finding and completion of food composition data bases.

How Good Are the Data that Do Exist?

There is considerable variability in the quality of food composition data, and rarely is information about data quality available to the user (paper 18). It appears that the individual data that make up food tables and data bases have often undergone only limited scrutiny. While major tables choose their sources carefully and document these sources, this is expensive and time consuming, and many data-base compilers do not give sufficient attention to this problem, leaving the responsibility of data quality to those from whom they acquire data. Similarly, estimation of data to fill in gaps in tables is frequently not performed with sufficient care, nor are these procedures documented, partly because of the lack of accepted guidelines. Clearly one conclusion that must be drawn from these considerations is that users must use food composition data cautiously.

Before considering how to improve the quality of food composition data, it must be pointed out that most variability in that data is not due to analytic error (papers 2 and 19). Of the number of factors that influence the observed levels of components in foods, it is true that several can be considered error, and their contributions to the overall variability of food composition data evaluated, categorized and, in some cases, minimized. For example, the analytical procedures introduce variability which can be minimized by following good laboratory techniques [11].

However, many other sources of nutrient variation are inherent in the foods themselves. These include geographical region of production, cultivar/species, changes in fortification levels, and agricultural practices in general [1]. Studies are needed to identify, characterize, and evaluate these several sources of variation to permit data compilers to provide users with food composition data that are less variable, perhaps through subdivisions of existing food categories regional tables, dated values, and so forth.

The two general areas where major efforts are needed to improve the situation with regard to the quality of food composition data are: (a) improvement of the quality of the data per se, and (b) improvement of communications so that the user will be able to determine the quality of specific data of interest.

Improving Quality of Data

The long-range improvement of the quality of food composition data can best be achieved through amelioration of the measurement system (improvement of sampling techniques and analytic methods, development of standards for generating food composition data, development of training programmes in food analysis, and use of biological reference standards) and standardization of the procedures for manipulating data, including those for estimating data that are not directly available as analytic determinations. These are all essential efforts that will contribute to the reduction of the errors in food composition data.

Improving the Documentation of Quality of Data

Another area in which the field of food composition data demands a major effort is that of documenting more carefully the "context" of the data - those factors which can, and do, contribute to the variability of the data. This is essential so that users can be made aware of the potential problems of the data, and be given enough information to judge for themselves whether the data are of sufficient quality for their needs.

Additionally, there is a need for the development of an overall scheme to indicate the reliability of data (see paper 18 for a detailed discussion of this topic). For example, Exler [3] has described, and used, a procedure for evaluating existing data against fixed standards to produce a score, or "confidence code," for each data set. These confidence codes not only give the users of the data an indication of their reliability but also inform data generators where new data are needed, as well as providing data compilers with tools to rationally combine new food composition data with existing data.

Thus, food composition data are of uneven and often unknown quality, and users approach them with due recognition of this problem. Moreover, they must be aware of both the inherent variation in food composition data and the variation that can be introduced by the gathering and manipulating of data. Every effort must be made to make available to the user information concerning the food and its analysis that will provide insight into the reliability of the data and its suitability for a particular purpose.

How Accessible Are the Data?

The accessibility of food composition data is obviously essential to its usage, and has three key aspects: (a) finding the data (if they exist), (b) obtaining those data, and (c) determining the precise meaning of the data obtained.

Finding the Data

Determining whether the desired data exist and finding where they are located is discussed above and, as pointed out, represents a significant problem. Currently there is no complete, up-to-date, global catalogue of food composition data. It should be emphasized that the effort involved in compiling and keeping current such a catalogue, which includes enough information to be widely useful to the various user groups, is a major undertaking.

Obtaining the Data

The question of moving the data around - data interchange - is also a major problem because of the time and effort that must be devoted to the actual acquisition of food composition data tables must be entered manually into the user's system, or programs custom-written to read specifically formatted tapes or disks. As the situation becomes more complex, with more generators, compilers, and users of data, the problems of data interchange will increase; and therefore dealing with them will consume more of the users' resources. Thus a major, essential task is the development of standardized guidelines for food composition data interchange.

Identifying the Data

Precisely identifying the data - determining exactly what food and what nutrient the numbers represent (the question of standardized terminology) - is key to the criticaluse of food composition data (paper 6). A standardized food-naming and classification system is critical to data entry, interchange, and retrieval, and currently no acceptable scheme exists. Although there are common elements that appear in the naming systems in most food composition tables, true compatibility does not exist even among the most commonly used data sets. The development of a standardized global terminology for food composition data which addresses the associated problem of classification is an important task that needs to be initiated and accomplished as soon as possible.

A food composition data system

Users obviously need more than just data - they need the machinery to interact with these data. This aspect of the subject can be discussed under the rubric "food data systems," used to describe the data and all the programmes or tasks involved in keeping the data relevant and available to the user.

The first point to be made is the distinction between those data bases and systems that are tailored for a single specific purpose or task, and those that attempt to be general purpose. This distinction is discussed at length by Hoover (paper 10) in terms of two tiers of users. It is important to note that the specific data bases are constructed from the general, and the validity of special-purpose data bases depends on the validity of both the data in the general data base and of the procedures by which they were selected.

The design and building of specific-purpose nutrient data bases and systems are straightforward since such systems can usually be completely defined in advance (although in fact they rarely are). Additionally, the actual data involved are usually fixed for the duration of the task. Much of the design effort here is focused on the user interface - making the system easy to use. A number of commercial firms supply such systems [5, 6]; however, a standard problem is that documentation of the source and quality of the data is frequently missing, leaving the user without guidance in this area.

General or broad-purpose nutrient data systems tend to focus on the data rather than on the details of interface with the user, although all systems must address this latter aspect. A number of papers given at the conference address the management issues (papers 7, 10, 12, and 13), others describe the magnitude and complexity of the task (papers 11, 15, and 17), and paper 21 focuses on the tools and concepts available to the system designer. The major points are summarized below, organized into the three categories of (a) the data themselves, (b) documentation of the data, and (c) preparation of subsets of the data.

The Data Themselves

The ideal general-purpose data base contains all the data that anyone might need, in a form that makes them readily accessible for any purpose. To approach this ideal it is necessary to be concerned with the following areas.

Data Acquisition

The data base must be updated continually and aggressively with new foods and new analyses, including re-analyses with better techniques, analyses of new products on the market, and new formulations of existing products. Thus standardized procedures must be implemented for routine collection of new nutrient information from available sources, including governmental publications, the scientific literature, and manufacturers'data on commercial products.

Data Consistency

An important aspect of adding data to a data base is that each new piece of data must be carefully evaluated for reliability. Moreover, all nutrient data files should be routinely checked for consistency, to identify possible anomalies and errors in the data. Such procedures could include, for example, comparing nutrient values within food groups or comparing actual data with predicted values. Thus the sum of the weight of the macro-nutrients plus ash and water theoretically should be 100 grams, while the sum of the calorie contributions of each macronutrient (including alcohol) can be compared with the total value for calories.

Having confidence in the individual data is one aspect of the question of the reliability of a data base. A cheek on the working of the entire data base, including a cheek on calculation procedures, can be provided by calculation of a selected, carefully constructed set of dietary records [7]. Such a test should be routinely carried out, with disagreement between successive runs carefully investigated and explained.


General-purpose data bases need to contain information about the source and quality of each of their data points. At a minimum, the user should be able to trace back each piece of data either to a source document or, in the case of analytic data, a laboratory reference; or, if it is estimated, it should be possible to ascertain just how this was done and from what other data. Moreover, it is important to maintain older data as part of the system. In the case of foods and food preparations which have been modified or are no longer on the market, data should be retained for comparison purposes, and so that dietary information collected in the past can be evaluated.

Preparation of Data for the Ultimate User

A major responsibility of the general-purpose data system is to prepare subsets of its data for the "front-line" users - these are the special-purpose data bases mentioned above. In order to do this at all well, such a system must support a flexible query language, an information data base that adequately describes the data, and sufficient manipulative machinery. Areas of specific importance are:

Access to the Data

The system should provide a variety of different ways to access the data. For example, foods should be indexed by food group and type of processing and preparation undergone, as well as by common name and food code number. Moreover, linkages to other data, such as foodspecific quantity units, are also an essential part of retrieving the necessary data.

Aggregation of Data

Many users require data on quite general foods (for example, "apples" rather than "Red Delicious apples"). A general-purpose data base often contains some of these entries, with nutrient levels estimated by combining the data of several specific foods for which analytic data exist. It is essential that the data base include information on just how these estimations were calculated, and, further, that it provide the information, and perhaps the machinery, necessary for the users to make further combinations of data to suit their specific purposes.

Data Presentation

Presentation of data, either on a screen or in hard-copy reports, needs to be flexible to permit the design of special-purpose formats to meet specific user needs. For example, options for presentation of data should permit the display of calculated nutrients as a percentage of calories, or other calculated combinations of nutrient values, such as saturated fat as a percentage of total fat or in ratio to polyunsaturated fat. Other options might include comparison of calculated nutrient intakes with recommended standards for specific age-sex groups, or the reporting of nutrients for each individual food item, for single meals, for single days, or for the average of multiple days.


This conference reviewed the field of food composition data from the point of view of the user. A number of areas of concern were discussed and some specific issues raised concerning the development of the field. The conference was convened by INFOODS in part to gain insight into what INFOODS itself should be doing in the future. To this end it formulated a number of specific recommendations for INFOODS activities:

1. People working with the diverse aspects of food composition data are not strongly aware of the similarities of their efforts and of the issues they must deal with. This has led to a tradition of independent activities resulting in incompatibilities and duplication of effort. INFOODS is encouraged to work to develop a sense of community within the field. This effort, in part, involves communication, and it is therefore recommended that INFOODS publish a Journal of Food Analysis and Composition as well as compile international directories of food composition data and of workers in various facets of the field.

2. Standards or guidelines are needed in several areas:

- data gathering: a manual detailing sampling and analytic methods for the gathering of food composition data;

- terminology: comprehensive, international terminology for describing food composition data, especially the naming and classification of foods;

- data interchange: a standardized scheme for the interchange of food composition data to facilitate the movement of such data around the world;

- data manipulation: standardized statistical and mathematical procedures for manipulating data, especially in the areas of summary statistics and imputation of missing data;

- usage: suggestions on how food composition data should be utilized in various areas, such as epidemiology and dietary counselling.

3. Recently, attention has focused on the variability of human consumption and of human requirements for nutrients. This variability is complemented by the variability of food composition, an area which has been little studied and is poorly documented. This entire area of food data variability, reflecting inherent differences in foods as well as differences of analytic methodology, needs to be carefully studied, with special attention paid to identifying, measuring, and evaluating the components of variability, and additional attention to documenting and minimizing it where possible.

4. A major goal for the next few years is to make food composition data easily available on an international basis. It appears, however, that there may be legal difficulties developing. There are a number of consultants, companies, and even countries that produce and market data bases and food computer systems. These individuals and organizations are becoming aware of the commercial value of food composition data, and there are suggestions that the users of food composition data may soon have to deal with legal obstacles to the free interchange of their data. As such developments are monitored, these problems, and the users' options in response, need to be explored. A related problem, in the sense that it is a legal problem, is that of the responsibility for the accuracy and updating of data files. The question of who is legally responsible for errors that might result from calculations based on data bases is one that has arisen in other fields, and may well arise in the area of food composition data.

In summary, the participants at the INFOODS Users and Needs conference strongly supported the purpose and goals of INFOODS, offered the suggestions outlined above for what INFOODS should do, and urged INFOODS to begin working on them speedily.


1. R. Bressani, "The Data Required for a Food Data System," Food and Nutrition Bulletin, 5(2): 69-76 (1983).

2. A. Bruce and L. Bergstrom, "User Requirements for Data Bases and Applications in Nutrition Research," Food and Nutrition Bulletin, 5(2): 24-29 (1983).

3. J. Exler, Iron Content of Food, Home Economics Research Report, no. 45 (USDA, Human Nutrition Information Service, Washington, D.C., 1982).

4. FAO, Food Composition Tables, Updated Annotated Bibliography (FAO, Nutrition Policy and Programmes Service, Food Policy and Nutrition Division, Rome, 1975).

5. D. M. Hildebrandt, Computer Programs and Databases in the Field of Nutrition. A Partial List, 4th ed. (University of Washington, Academic Computing Center, Seattle, Wash., 1985).

6. L. W. Hoover, ea., Nutrient Data Bank Directory, 4th ea., Ninth Annual National Nutrient Data Bank Conference, Amherst, Mass. ,18 20 June 1984 (Curators of University of Missouri, 1984, with supplement, 1985).

7. L. W. Hoover and B. P. Perloff, Model for Review of Nutrient Database System Capabilities (University of Missouri-Columbia Printing Services, Columbia, Mo., 1984).

8. International Network of Food Data Systems, International Directory of Food Composition Tables, 1st ed. (MIT, Cambridge, Mass., 1986).

9. W. M. Rand and V. R. Young, "Report of a Planning Conference concerning an International Network of Food Data Systems (INFOODS)," A.J.C.N., 39: 144-151 (1984).

10. D. A. T. Southgate, "Availability of and Needs for Reliable Analytical Methods for the Assay of Foods, "Food and Nutrition Bulletin, 5(2): 30 39 (1983).

11. D. A. T. Southgate, Guidelines for the Preparation of National Tables of Food Composition (Karger, Basel, 1974).

12. K. K. Stewart, "The State of Food Composition Data: An Overview with Some Suggestions," Food and Nutrition Bulletin, 5(2): 54-68 (1983).

13. J. E. Vanderveen and J. A. T. Pennington, "Use of Food Composition Data by Governments," Food and Nutrition Bulletin, 5(2): 40-45 (1983).

14. C. T. Windham, R. G. Hansen, and B. W. Wyse, "Uses of Nutrient Data Bases for Identifying Nutritional Relationships to Public Health and Nutrition Education in the United States," Food and Nutrition Bulletin, 5(2): 46-53 (1983).

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