Iodine in food- and dietary supplement-composition databases.

The US Food and Drug Administration (FDA) and the Nutrient Data Laboratory (NDL) of the USDA Agricultural Research Service have worked independently on determining the iodine content of foods and dietary supplements and are now harmonizing their efforts. The objective of the current article is to describe the harmonization plan and the results of initial iodine analyses accomplished under that plan. For many years, the FDA's Total Diet Study (TDS) has measured iodine concentrations in selected foods collected in 4 regions of the country each year. For more than a decade, the NDL has collected and analyzed foods as part of the National Food and Nutrient Analysis Program; iodine analysis is now being added to the program. The NDL recently qualified a commercial laboratory to conduct iodine analysis of foods by an inductively coupled plasma mass spectrometry (ICP-MS) method. Co-analysis of a set of samples by the commercial laboratory using the ICP-MS method and by the FDA laboratory using its standard colorimetric method yielded comparable results. The FDA recently reviewed historical TDS data for trends in the iodine content of selected foods, and the NDL analyzed samples of a limited subset of those foods for iodine. The FDA and the NDL are working to combine their data on iodine in foods and to produce an online database that can be used for estimating iodine intake from foods in the US population. In addition, the NDL continues to analyze dietary supplements for iodine and, in collaboration with the NIH Office of Dietary Supplements, to publish the data online in the Dietary Supplement Ingredient Database. The goal is to provide, through these 2 harmonized databases and the continuing TDS focus on iodine, improved tools for estimating iodine intake in population studies.

Variation in the iodine concentrations of foods: considerations for dietary assessment.

BACKGROUND: Food-composition tables typically give measured nutrient concentrations in foods as a single summary value, often the mean, without providing information as to the shape of the distribution. OBJECTIVE: Our objective was to explore how the statistical approach chosen to describe the iodine concentrations of foods affects the proportion of the population identified as having either insufficient or excessive iodine intakes. DESIGN: We used food intake data reported by the 2009-2010 NHANES and measured iodine concentrations of Total Diet Study (TDS) foods from 4 US regions sampled in 2004-2011. We created 4 data sets, each by using a different summary statistic (median, mean, and 10th and 90th percentiles), to represent the iodine concentration distribution of each TDS food. We estimated the iodine concentration distribution of each food consumed by NHANES participants as the 4 iodine concentration summary statistics of a similar TDS food and used these, along with NHANES food intake data, to develop 4 estimates of each participant's iodine intake on each survey day. Using the 4 estimates in turn, we calculated 4 usual iodine intakes for each sex- and age-specific subgroup. We then compared these to guideline values and developed 4 estimates of the proportions of each subgroup with deficient and excessive usual iodine intakes. RESULTS: In general, the distribution of iodine intakes was poorly characterized when food iodine concentrations were expressed as mean values. In addition, mean values predicted lower prevalences of iodine deficiency than did median values. For example, in women aged 19-50 y, the estimated prevalence of iodine deficiency was 25% when based on median food iodine concentrations but only 5.8% when based on mean values. CONCLUSION: For nutrients such as iodine with highly variable concentrations in important food sources, we recommend that food-composition tables provide useful variability information, including the mean, SD, and median.