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were discussed in Chapter 8. Some of these topics are revisited now and specific areas in which research is still needed are identified.

Perhaps one of the most important advances to improve application of human nutrient requirement estimates has been the further development and refinement of statistical procedures to reduce if not eliminate the distorting effect of random error in dietary data. What has become apparent in dealing with the random error is that the remaining issue of paramount importance in dietary data collection and analysis is the presence and true extent of bias (such as under- or over-reporting of food intake). The same amount of effort that went into determining statistical approaches for estimation and reduction of the effect of random error should be directed toward the estimation and amelioration of bias. This is a relatively unexplored field. Methods for directly estimating bias regarding energy intake have been developed and used to demonstrate that the problem is serious. Efforts have begun in the management of bias during data analysis but these are far from satisfactory at present. The handling of bias is seen as a very high-priority area awaiting new initiatives and innovative approaches.

Another area of need is behavioral research to determine why people under-report food intake. Advances in this area would allow development of improved dietary data collection tools that would not trigger this behavior. Such information would also help in the derivation of statistical tools to correct the bias associated with this phenomenon.

Better ways to quantify the intake of supplements are needed. Methods for collecting accurate supplement intake data have not been widely investigated. For the Third National Health and Nutrition Examination Survey, different instruments were used to collect food intake data and supplement intake data, and the correct methodology for combining these data is uncertain. Furthermore, the intake distribution from supplements usually cannot be adjusted because the current data do not permit the estimation of the day-to-day variability in supplement intake. Despite the difficulties in maintaining a supplement composition database for the rapidly changing market, investigation of better methods of quantifying supplement intakes is a high-priority research area.

Food composition databases need to be updated to include the forms and units that are specified by Dietary Reference Intakes (DRIs). Chemical methodology to facilitate analysis of various forms of certain nutrients (e.g., α-vs. γ-tocopherol) may be required. The DRI recommendations also imply that databases need to separate nutrients inherent in foods from those provided by fortification,

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