|Food Composition Data: A User's Perspective (UNU, 1987, 223 pages)|
|Report and recommendations of the conference|
The users and their needs
Food composition data
A food composition data system
INFOODS was organized after a meeting of experts concerned with the unsatisfactory state of food composition data at the international level . It was formed in response to a perceived sense that there were major problems in the area of food composition data, and therefore one of its first tasks was to determine the status of food composition data, and to decide which users' needs were not being met and what should and could be done. Thus, INFOODS helped organize a meeting involving a number of individuals directly concerned with food composition data. This was held on the campus of Utah State University in late March 1985, with the major goals being to define and document the current situation, and to make proposals for the future. (See the appendix for a list of the participants.) The format of the meeting included presentation of papers followed by discussion by the full group; small writing groups then prepared the material on which this report was based. After the meeting the authors were given the opportunity to revise their papers, and these papers follow this report of the conference. The report itself is divided into sections that introduce the papers (section 1), discuss the users themselves and their needs (section 2), examine the data that are available (section 3), explore the design of an ideal food composition data system (section 4), and finally make recommendations to INFOODS for future activities (section 5).
The papers presented can be divided into five general areas. The first three papers, each by a member of the INFOODS staff, deal with the background and general context of the meeting. Vernon Young (paper 1) discusses the forces that led to the formation of INFOODS, arguing that it is now time for the field of food composition data to be drawn together and, particularly, to consider agreed-upon, unified, and standardized approaches to its problems. These problems arise from a chaotic situation wherein everyone seems to be working independently. Much of the food composition data that exist are incomplete, incompatible, and inconsistent. William Rand (paper 2) presents some general ideas of food composition data as data, with emphasis on its variability and its inherent incompleteness for solving specific problems. This paper points out some of the consequences of the current situation of incompatibility and inconsistency between data bases, with special attention to the lack of confidence in the whole field of food composition data. John Klensin (paper 3) presents the role of INFOODS as a "broker" of food composition data, helping to increase the accessibility and interchange of data, and co-ordinating the development of guidelines. A major point made by this paper is that the users should define the systems they need, and that computers should be viewed as tools to assist the user rather than as constraints.
The second group of papers is concerned with specific uses of food composition data. Ann Sorenson of the US Department of Health and Human Services and her colleagues at the University of Pittsburgh (paper 4) report on a number of international epidemiological research programmes, the problems they have with existing food composition data, and the implications for how food composition data should be organized and managed. Lenore Arab of the University of Heidelberg (paper 5) discusses her experience working in the area of nutritional epidemiology in Europe, focusing on practical problems and potential solutions that range from the difficulties of determining dietary intake to those of dealing with data from several different food tables, each with its own conventions. Ritva Butrum of the US National Cancer Institute (paper 6) presents many of the Institute's programmes, both within the United States and internationally, which require food composition data, and the problems that these programmes face without globally complete, consistent, and compatible data. Betty Peterkin, of the US Department of Agriculture (paper 7), shows how the data that USDA collects are used to satisfy various programmes in research, information, education, regulation, and food assistance, with special attention given to the assessment of the quality of the US diet and preparation of dietary guidelines. This paper lists differing aspects of food composition data which individual users require: sets of nutrients, various stages of processing or preparation, levels of statistical analyses, degrees of precision and accuracy, units of measure, and different formats. Carol Windham and her colleagues at Utah State University (paper 8) discuss the needs that university research in the areas of nutrition guidance and nutrition education place on food composition data. The paper also describes the components of and problems with the system that Utah State University and the Human Nutrition Information Center of USDA developed to fulfil these needs. The need for more and better data, and the importance of documentation to characterize the data, are stressed. Fred Steinke of the Ralston Purina Company (paper 9) discusses the uses that food companies make of food composition data, surveys the data that are currently being used, and maintains that safety and acceptability by the consumer are the primary concerns of the food industry.
The third group of papers is authored by developers, managers, and users of large food composition data bases. Loretta Hoover of the University of Missouri-Columbia (paper 10) discusses the general status of nutrition data bases within the United States in the context of the requirements and problems that the user faces in dealing with these systems. She introduces the concept of two tiers of users: those experienced users who are primarily interested in issues of accessibility, installation, updating, availability, and computational concerns as well as being aware of the problems of accuracy and applicability of different software and data bases; and those inexperienced users who are primarily interested in utility, compatibility, and cost. Any efforts to improve the status of food composition data need to be directed primarily toward the first tier of users; however, the results of improvement will shortly effect those in the second tier. Frank Hepburn of USDA (paper 11) describes the management of the USDA data base, illustrating how the data has evolved in response to a changing food supply and the more sophisticated needs of users. Marilyn Buzzard and Diane Feskanich of the Nutrition Co-ordinating Center at the University of Minnesota (paper 12) describe their system and the procedures that they have initiated to satisfy user needs. The specific needs stressed include: standardized methods of obtaining data; up-to-date and complete nutrient profiles; adequate documentation of data sources; quality control for the data base itself; and stability, comparability, and flexibility. Grace Petot of Case Western Reserve University (paper 13) discusses the management of a large academic system, cataloguing user needs and expectations.
The fourth group of papers is concerned with food composition data outside the United States. Hernando Flores of the Federal University of Pernambuco, Brazil (paper 14) illustrates the very real problems which arise from using the outdated INCAP tables to estimate consumption of important nutrients. Aree Valyasevi of Mahidol University, Thailand (paper 15) describes the status of food composition data in Asia, and reports on progress in the establishment of ASIAFOODS. Ake Bruce and Lena Bergstrom (paper 16) catalogue the data bases within Sweden and other Nordic countries, showing the profusion of data bases that can exist in a relatively homogeneous part of the world. Pamela Verdier of Health and Welfare Canada (paper 17) describes the national data base of Canada, how it was put together and managed, and how it is integrated into the nutritional activities of Canada.
The fifth and last group of papers discusses food composition data from several points of view slightly removed from the field. Joanne Holden and her colleagues at the Beltsville Nutrient Composition Laboratory of USDA (paper 18) discuss the problems of maintaining the quality of the data in data bases and of assessing and communicating that quality. This paper presents a specific system for evaluating published data on selenium, and discusses the aspects such a system must consider. George Beaton of the University of Toronto (paper 19) examines the effect of uncertainty in food composition on the estimation of nutrient intake from food consumption surveys, concluding that this variability is often less important than previously assumed. Reliability of food composition data is most important in those foods that make the greatest contribution to total nutrient intake, and the effect of improving reliability will be most evident when examining diets which include few foods. This paper also notes that these considerations focus on variability and that the presence of bias in the data is often an important source of error. Catherine Woteki of the US National Center for Health Statistics (paper 20) discusses in detail the US National Health and Nutrition Examination Surveys, which are a major user of the USDA data base. John Klensin of INFOODS (paper 21) examines food composition data bases from the point of view of modern information systems theory and practice, showing that the field has changed considerably since most data bases were first implemented.
The Users of Food Composition Data
Data on the composition of foods are used by a wide selection of individuals and organizations, ranging from the Food and Agriculture Organization of the United Nations, which calculates food balance sheets for countries around the world and advises them on the global allocation of foods and other resources, to individual shoppers reading labels in the supermarket in an attempt to plan the nutritional value of their next meal. The following list of examples illustrates the range and variety of users (see also the extended list in paper 13).
International Users (e.g. paper 15)
International agencies dealing with food aid are responsible for acquiring large quantities of food and transporting it to different locations in the world, often to meet the specific nutritional needs of populations. Here there is a strong need to know the constituents of the foodstuffs available around the world and, at the same time, the relevant nutrient situation within each country, in order to match the food supply to human physiological needs.
Governments need to know the composition of the foods that are imported in order to plan for satisfying the nutritional requirements of their populations and to protect these populations from contaminant and toxicologically active constituents.
Food industries that compete on the international market need to know the components of the local food with which they are competing, and also the nutrient content of potential ingredients for their products - ingredients which may come from widely separated parts of the world.
Epidemiologists have long realized that food is one of the most important components of an individual's environment. Studies of global disease patterns must be accompanied by data on global food and nutrient consumption patterns (see papers 4, 5, and 6).
National Users (e.g. papers 16 and 17)
National governments regulate what is produced within the country as well as what is imported in order to protect and guarantee the health of their populations . Their activities include the setting of regulations and the monitoring of adherence to those regulations. They must also assess the nutritional status of their populations (papers 7 and 20); one important aspect of this is to determine what is being consumed and how this compares with established dietary requirements and allowances. All of these activities require the availability of reliable and extensive data on the composition of foods.
National programmes of feeding, such as in schools or in the military, require up-todate information on the nutrient content of foods so that nutritionally adequate diets can be formulated.
University teachers and researchers require reliable and current food tables for a broad spectrum of activities that involve the relationship between health and disease and what people consume [2,14] (papers 8 and 14).
Below the national level, there are many activities concerned with the preparation and recommendation of healthy diets, in institutions such as hospitals and factories as well as in special segments of society such as the elderly.
Food industries regulate the quality of their foods by routinely analysing the components of their products, using available food tables. New formulations must adhere to nutritional and safety standards and food tables are used initially to select preparations for investigation (paper 9).
The diet and nutrition clinics which continue to increase in number in technically developed regions rely heavily on food tables for individual counselling. These clinics complement the activities of individual dietitians and physicians dealing with patients ranging from those with metabolic disorders to those who are over- and underweight.
Finally, the most extensive use of food composition data by the individual is, of course, the individual shopper scanning the ingredients list, nutrient contents, and percentages of requirements fulfilled on the labels of packaged foods.
Some Generalizations about Users
The extent and diversity of the users of food composition data are underlying problems of the field. These various users' groups not only make very different uses of the data, but also have different expectations and requirements. Thus it is important to identify the common threads that would permit the organization of users into groups who have similar needs and make similar demands on any food composition data system:
- System requirements are quite different for the user concerned with a limited set of foods that can be fairly well defined, such as those in a restricted geographic region or those suitable for a very specific diet, and for the user concerned with extensive, perhaps open-ended, sets of foods, with often a global distribution. The former group of users is usually able to define its needs and knows the questions it will ask of a data base, which can thus be embedded in a fairly rigid system, while the latter requires much more flexibility in its interactions with the data.
- The degree of precision or specific level of detail required divides users into a spectrum of groups, with some needing accurate data, some only approximate data or ranges, and others only an indication as to the presence or absence of components. - Many users need to know the constituents of specific foods (e.g. diet evaluation) while others are interested in the foods that contain certain components (recipe or menu development). This distinction divides the users into two groups with quite different search and retrieval requirements.
- The distinction between whether the user is interested in a specific individual, for example for diet or menu planning, or in a group of individuals, for example to determine the nutritional intake of the population of a region, is essential in order to design a system to properly estimate various statistical quantities, such as confidence regions.
- Some users need only representative values for specific nutrients in specific foods. Others are interested in the extremes that a nutrient can attain (at a certain probability level), while others want to know how certain nutrients (and foods) correlate with one another. Each of these classes of users asks different questions, requires different amounts and types of data, and needs systems for usage which are superficially quite different.
The Needs of Food Composition Users
The basic needs of the users are: (a) high-quality data on foods and components, (b) ancillary data, and (c) facility of access and manipulation of these data to give the information desired.
The most obvious need of the users is for data that represents the foods and components with which they are concerned. These data must be as precise as the particular usage requires, unambiguously identified, and easily accessible (see section 3 below).
For most users, the amount of a specific nutrient in a given specific food is not sufficient for their task (paper 2). Necessary ancillary data range from usual serving sizes to household consumption and individual nutrient requirements. The following list includes some of the major types of additional information that often may be needed:
- data describing the food composition data - where they came from, their quality, etc.;
- descriptions of representative serving portions, including weight/portion equivalents;
- brand names and identifications; recipes and ingredient lists;
- effects of processing and preparation; fortification rules;
- food/nutrient interactions; food/drug interactions;
- contaminants, toxicants, and allergenic compounds; dietary standards and nutrient requirements;
- food production and consumption; geographic distribution of disease.
The mere existence of food composition and associated data is not sufficient for carrying out the tasks of most users. These data need to be acquired, merged, and manipulated in order to be turned into information. Thus the users require many of the tools of data-base management, with their use-specific tasks ranging from recipe calculations to grouping and imputation; these are discussed more fully in section 4 below. It is especially important to note that, with the ever widening usages of food composition data, and with the increasing availability of those data, it is essential that there be consistency in the way these tasks are performed.
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 . 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 . 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 . Additionally, Darlene Hildebrandt, of the University of Washington in Seattle, issues a listing of Computer Programs and Databases in the Field of Nutrition .
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.
The components of foods that are most frequently missing include:
- nutrients (especially trace minerals, some B vitamins, and lipid-soluble
- 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.
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 . 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 .
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 . 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  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.
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.
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.
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 . 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.
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).
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