TITLE: WEB-BASED RESOURCES FOR ENHANCINGDIETARY DATA ANALYSIS: WHAT WE EAT IN AMERICA,NHANES

AUTHOR(S): Jaspreet Ahuja; Nancy Raper, MS; CeciliaWilkinson Enns, MS; Randy LaComb, MS; Food Survey ResearchGroup, ARS, USDA, Beltsville MD

KEYWORDS: What We Eat In America, NHANES, dietary data,FNDDS, What’s In The Foods You Eat, time trends

OBJECTIVE: To enhance researchers’ ability to analyze dietaryintake data, resources available on USDA’s Food SurveysResearch Group website will be highlighted, along with examplesof their applications.

METHODS: The USDA Food and Nutrient Database for DietaryStudies (FNDDS) is used to process the What We Eat In America(WWEIA), NHANES dietary intake data. The FNDDS includescomprehensive information for coding individual foods andportion sizes and contains nutrient values for calculatingnutrient intakes. The Multi-year FNDDS permits tracking ofchanges in foods over time, because it differentiates betweenchanges due to data improvements versus real changes in foods.Improved values replace older values; real changes have datesindicating the time period for each value. The What’s In TheFoods You Eat Search Tool is an easy-to-use searchable versionof the FNDDS.

RESULTS: Researchers may access all resources on the FSRGwebsite at http://www.ars.usda.gov/ba/bhnrc/fsrg. Updatedversions are released every 2 years, in parallel with the releaseof WWEIA data.

SIGNIFICANCE: These tools will benefit not only researcherswho analyze WWEIA data, but also those who may apply themin their own studies.

TITLE: USING A MODIFIED VERSION OF THE USDA’SAMPM SOFTWARE: THE CANADIAN EXPERIENCE

AUTHOR(S): Josephine Deeks; Maya Villeneuve; IsabelleMassarelli; Paula Roach; Isabelle Rondeau; Health Canada, FoodDirectorate, Ottowa, Ontario, Canada

KEYWORDS: AMPM, survey, nutrition

OBJECTIVE: To customize the USDA Automated Multiple-PassMethod (AMPM) for 24-hour recall data collection in theCanadian Community Health Survey–Nutrition (CCHS 2.2).

METHODS AND MATERIALS: This software was chosen formany reasons: manual data collection was not possible due to thelarge sample size; the high cost of developing a new datacollection tool; type of interviewers utilized; and compatibilitybetween the US and Canadian food composition databases.Modifications included: addition of Canadian brands and foods,metric measures, and French translation.

RESULTS: Too many choices in the look-up tables (LUT) led towrong food selections. The advantages of the Trigram searchwere lost when both languages appeared jointly in the main foodlist (MFL) and LUT. Interviewers had difficulties navigatingthrough some challenging situations and the tool was used, forthe first time, weeks after training.

SIGNIFICANCE: The USDA AMPM is an excellent tool for 24-hour recall data collection. The process has been initiated byHealth Canada to maintain and update the tool for futurenutrition surveillance and research activities. Modifications willbe implemented to resolve the challenges encountered during theCCHS 2.2. Separating the French from English in the MFL andLUT, restoring the Trigram search, adapting questions inproblematic categories, and narrowing possibilities of answers inLUT would reduce errors and improve accuracy of this valuabletool.

TITLE: DEVELOPING A DATABASE AND A FOCUSED FOODFREQUENCY QUESTIONNAIRE FOR ASSESSING DIETARYARSENIC INTAKE FOR A BI-NATIONAL ARSENIC EXPOSURESTUDY

AUTHOR(S): Ellen J Graver, MS; Robin Harris, PhD, MPH;Vern Hartz, MS; Robin Whitacre, BS; Cynthia A Thomson, PhD, RD;Jason Roberge, MPH; Katie Holton, MPH; Graciela Caire; ArizonaCancer Center, Tucson AZ

KEYWORDS: arsenic FFQ, arsenic database

OBJECTIVE: Arizona and Sonora, Mexico investigators areevaluating associations between elevated arsenic (As) exposure andselected genetic polymorphisms.

DESCRIPTION: An inorganic As database was developed to be usedin conjunction with a focused As Food Frequency Questionnaire(FFQ). It was derived from the 1999 Market Basket Survey (MBS) ofInorganic As in Food. Forty MBS commodities were matched with 40lines on the focused As FFQ. The mean concentration of As in each ofthe 40 foods on the As FFQ represent the average concentration of Asthat a person would be exposed to after repeated consumption of thatfood over a one year period. An analysis program to connect Asdietary data from the As FFQ and the As database was developed.Total daily average As exposures from food (g/day) for individualswere computed as the sum of the product of the mean residueamount per serving size (g/day) of each food reported by eachindividual. This interviewer-administered, English and Spanish, 40-line item, 2-page scannable instrument assesses dietary inorganic Asintake over a previous 12-month period. Respondents answerquestions related to number of servings consumed and whether theirserving size was small, medium, or large. A reference portion size isprovided for the medium portion.

SIGNIFICANCE: This instrument and database may be useful inepidemiological studies of the associations between potentialenvironmental As exposures and cancer.

TITLE: UPDATING NUTRIENT INTAKE ESTIMATES FROMTHE ARIZONA FFQ: THE “METABOLIZE” NUTRIENTDATABASE

AUTHOR(S): Robin Whitacre, BS; Ellen J Graver, MS; VernHartz, MS; Stephen Joel Coons, PhD, RPH; Cynthia A Thomson,PhD, RD; Arizona Cancer Center, Tucson AZ

KEYWORDS: nutrient database, food frequency questionnaire

OBJECTIVE: The Food and Nutrient Database for Dietary Studies(FNDDS) 1.0 system, the National Health and NutritionExamination Survey (NHANES) national consumption data, andthe National Nutrient Database for Standard Reference (NDBSR)are the primary sources for the Nutrient Database used by aproprietary system (“Metabolize”) developed by the Arizona CancerCenter (University of Arizona) to map information from the ArizonaFood Frequency Questionnaire (AFFQ) to nutrients per day. Thisposter describes the development process.

DESCRIPTION: The FNDDS system only reports the 61nutrients for which there are values for all foods. The NDBSRreports values for 128 nutrients; however, not all foods havevalues for all nutrients. The FNDDS system was built so that itis possible to derive nutrient values using any version of theNDBSR. FNDDS 1.0 was based on NDBSR Version 16-1. UsingVersion 17, a new nutrient database was created.

SIGNIFICANCE: Using this approach, we have been able toexpand the available nutrient output (from 61 to 136 nutrients),phytochemicals, and food groups. Of course, caution must beused for nutrients for which there are missing data. In acomparison of AFFQ data run against the old and new“Metabolize” Nutrient Databases, only minor changes wereobserved in the macronutrients (�4.8% to �1.8%), and largerchanges were observed in the carotenoids (�25.6% to � 19.6%).Values were also derived for Isoflavones, Cruciferous grams, andRed Meat grams.

TUESDAY, SEPTEMBER 19

POSTER SESSION: NATIONAL NUTRITION DATABANK CONFERENCE

Journal of the AMERICAN DIETETIC ASSOCIATION / A-81