Comparing Calculated Nutrient Intakes Using Different Food Composition Databases: Results from the European Prospective Investigation into Cancer and Nutrition (EPIC) Cohort

Abstract

This study aimed to compare calculated nutrient intakes from two different food composition databases using data from the European prospective investigation into cancer and nutrition (EPIC) cohort. Dietary intake data of the EPIC cohort was recently matched to 150 food components from the U.S. nutrient database (USNDB). Twenty-eight of these nutrients were already included in the EPIC nutrient database (ENDB—based upon country specific food composition tables), and used for comparison. Paired sample t-tests, Pearson’s correlations (r), weighted kappa’s (κ) and Bland-Altman plots were used to compare the dietary intake of 28 nutrients estimated by the USNDB and the ENDB for 476,768 participants. Small but significant differences were shown between the USNDB and the ENDB for energy and macronutrient intakes. Moderate to very strong correlations (r = 0.60–1.00) were found for all macro- and micronutrients. A strong agreement (κ > 0.80) was found for energy, water, total fat, carbohydrates, sugar, alcohol, potassium and vitamin C, whereas a weak agreement (κ < 0.60) was found for starch, vitamin D and vitamin E. Dietary intakes estimated via the USNDB compare adequately with those obtained via the ENDB for most macro- and micronutrients, although the agreement was weak for starch, vitamin D and vitamin E. The USNDB will allow exposure assessments for 150 nutrients to investigate associations with disease outcomes within the EPIC cohort.

Lifestyle correlates of eight breast cancer-related metabolites: a cross-sectional study within the EPIC cohort

“…These questionnaires were validated through a calibration approach using a common 24-h diet recall [63] to adjust for possible systematic misclassification in dietary measurements, and a validation study using 24-h urine samples was conducted [64]. Despite these methodological efforts, however, potential measurement error may persist because of recall bias, misreporting of consumption for certain foods, or errors related to the food composition tables used (despite careful matching [15]). Nevertheless, several cross-sectional studies showing good correlations [65,66] between intakes measured by food questionnaires and expected specific biomarkers suggest that data from food frequency questionnaires can be used for the purposes of the present work.…”

“…Lifestyle and medical factors were assessed in the baseline questionnaire. Usual dietary intakes were assessed using center-or country-specific validated questionnaires covering the previous 12 months and matched to the US Department of Agriculture food composition database to estimate macronutrient intakes [15]. Glycemic index and glycemic load were computed.…”

Dietary intake and plasma phospholipid concentrations of saturated, monounsaturated and trans fatty acids and colorectal cancer risk in the European Prospective Investigation into Cancer and Nutrition cohort

“…EPIC food items were matched to the food composition database Release 26, developed by the United States Department of Agriculture (USDA) as part of the Nutrient Database for Standard Reference publications 25 (Release 26, October 2013, available at https://ndb.nal.usda.gov/ndb/). The method has been previously described 26 . The USDA database includes data for over 50 individual fatty acids and was used to calculate total SFA (∑ all cis 14:0, 15:0, 16:0, 17:0, 18:0, 20:0, 22:0, 24:0), total MUFA (∑ all cis: 16:1; 17:1; 18:1; 20:1; 22:1; 24:1), total iTFA (∑ trans ‐18:1; trans ‐18:2, trans , trans‐ 18:2) and total rTFA (∑ trans ‐16:1, trans ‐18:1n‐7; and conjugated linoleic acid, CLA).…”

Dietary fats and their sources in association with the risk of bladder cancer: A pooled analysis of 11 prospective cohort studies

“…Though this data was converted to grams per day using the United States Department of Agriculture (USDA) food composition database, the conversions were not country specific. Previous studies, however, suggested that the application of a common food composition database has advantages over the use of country specific food composition databases in that errors are consistent between the countries, hence making data more comparable 56 ; (b) unfortunately, data potential known BC risk factors, such as BMI, physical inactivity, socioeconomic status and occupational exposures to carcinogenic chemicals was missing. Moreover, it might be possibility that some lifestyle and/or environmental factor are associated with an individual's diet.…”