Data Analysis and Limitations

Whatever dietary assessment measure is used, the utility of the data is dependent on the translation of reported food intake to nutrient intake. This requires detailed and accurate nutrient databases. The US Department of Agriculture has the most extensive nutrient database in the world, allowing for good estimation of dietary intakes in the US. Most other countries have not conducted this level of food composition analysis for their own locations. Therefore, most databases used throughout the world have obtained at least some of their values from the US nutrient database, adding information as possible from locally analyzed products. However, because the nutrient composition of many foods, including fruits, vegetables, and even animal products can vary widely by growing conditions and specific subvariety, most available nutrient databases remain inadequate. Many use extrapolated values from similar foods when chemical analysis has not been completed. Furthermore, it is common for many country-specific databases to include information only on macronutrients and a few selected vitamins and minerals. The continual arrival of new manufactured products also complicates the upkeep and management of food composition databases.

Consequently, considerable database work remains to expand the utility of worldwide dietary surveys.

Once the nutrient data are calculated, data are generally tabulated to present age, sex and, sometimes, ethnic specific mean intakes and standard deviations. Further disaggregation by region, socioeconomic group, or other group characteristic can by very helpful in understanding the macro-distribution of nutrient intake and for targeting specific groups with nutrition intervention programs. If a complex survey design was used, or if systematic nonparticipa-tion was observed, sampling weights must be applied to adjust the means and standard errors.

Using the methods described above, estimates of the population with low intakes of specific nutrients are also calculated. Beyond these descriptive measures, comparison of nutrient intakes with individual characteristics and health measures generally requires multiple regression analysis with appropriate adjustment for potentially confounding variables. Again, when complex survey designs have been used, the inclusion of sample weights and appropriate adjustment of variances is needed. Specialized statistical software for use with survey data is available. In cases where a single recall has been used, substantial weakening, or attenuation, of associations is likely, but use of 'deattenuation' methods can, at a minimum, provide information on the likely extent of this attenuation. When food frequency data are used, it is important to include some validation methods, preferably with comparison to key biomarkers of nutritional status, but at least to multiple recalls on a subset. This is particularly true when a new questionnaire is being used, but is also important over time as the food supply and food habits change in the population.

See also: Dietary Intake Measurement: Methodology; Validation. Nutritional Assessment: Anthropometry; Biochemical Indices. Nutritional Surveillance:

Developed Countries; Developing Countries. Vitamin A: Biochemistry and Physiological Role.

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