| Food Composition Data: A User's Perspective (1987) |
|A system for evaluating the quality of published nutrient data: Selenium, a test case|
One of the purposes of developing this system was to encourage investigators to consider all five categories of criteria when designing studies and reporting results. The system is a dynamic one and can be modified to respond to improvements in such areas as analytical methodology and availability of SRMs as well as to the reporting of new data. As additional research is done that incorporates the top levels of these criteria' we expect to upgrade our standards to allow more stringent evaluation of published data, and thereby increase users' confidence. For example, the quantitation limit of the method was rarely reported in the studies we evaluated. Without this information, it is difficult to assess the validity of low Se levels in foods. Rating studies on this aspect of analytical method only when a quantitation limit was reported was a compromise based on the level of existing data. In future evaluations, it is hoped that a rating of 0 will be assigned in analytical method to those studies that do not report the quantitation limit of the method as well as to studies which report results below the stated quantitation limit.
Although the criteria were developed using Se as the test case, they are applicable to data compilations for other food components. The evaluation system becomes nutrient-specific with the customizing of the criteria and the scheme for deriving the QI and mean nutrient value. Use of this evaluation system for any particular food component requires these steps: collection of relevant papers; delineation of nutrient specific criteria at the various rating levels; assignment of ratings; and selection of strategies for deriving the QI and mean nutrient value. The quality of a given set of data influences the fitting of the criteria into the rating scale and the scheme selected for deriving the QI and mean nutrient value. This process is analogous to the familiar statistical problem of balancing type I and type 11 errors. If the rating scale is too rigorous, most available data will be eliminated. On the other hand, if it is too lenient, many less reliable studies will be included.
The delineation of levels of data quality permits data users to evaluate the suitability of a specific mean nutrient value for their data bases. Furthermore, access to criteria ratings that were assigned in the data evaluation procedure would allow the user of the data to assess the specific decisions made in the evaluation. The number of commercially available data bases is increasing as are the number of users. Data users must take on the responsibility of selecting nutrient data of known quality.