Lois Steinfeldt

A New Database Facilitates Characterization of Flavonoid Intake, Sources, and Positive Associations with Diet Quality among US Adults

BACKGROUND Epidemiologic studies demonstrate inverse associations between flavonoid intake and chronic disease risk. However, lack of comprehensive databases of the flavonoid content of foods has hindered efforts to fully characterize population intakes and determine associations with diet quality. OBJECTIVES Using a newly released database of flavonoid values, this study sought to describe intake and sources of total flavonoids and 6 flavonoid classes and identify associations between flavonoid intake and the Healthy Eating Index (HEI) 2010. METHODS One day of 24-h dietary recall data from adults aged ≥ 20 y (n = 5420) collected in What We Eat in America (WWEIA), NHANES 2007-2008, were analyzed. Flavonoid intakes were calculated using the USDA Flavonoid Values for Survey Foods and Beverages 2007-2008. Regression analyses were conducted to provide adjusted estimates of flavonoid intake, and linear trends in total and component HEI scores by flavonoid intake were assessed using orthogonal polynomial contrasts. All analyses were weighted to be nationally representative. RESULTS Mean intake of flavonoids was 251 mg/d, with flavan-3-ols accounting for 81% of intake. Non-Hispanic whites had significantly higher (P < 0.001) intakes of total flavonoids (275 mg/d) than non-Hispanic blacks (176 mg/d) and Hispanics (139 mg/d). Tea was the primary source (80%) of flavonoid intake. Regardless of whether the flavonoid contribution of tea was included, total HEI score and component scores for total fruit, whole fruit, total vegetables, greens and beans, seafood and plant proteins, refined grains, and empty calories increased (P < 0.001) across flavonoid intake quartiles. CONCLUSIONS A new database that permits comprehensive estimation of flavonoid intakes in WWEIA, NHANES 2007-2008; identification of their major food/beverage sources; and determination of associations with dietary quality will lead to advances in research on relations between flavonoid intake and health. Findings suggest that diet quality, as measured by HEI, is positively associated with flavonoid intake.

Monitoring Sodium Intake of the US Population: Impact and Implications of a Change in What We Eat in America, National Health and Nutrition Examination Survey Dietary Data Processing

Accurate monitoring of US sodium intake requires familiarity with national dietary data collection and processing procedures. This article describes a data processing step that impacts sodium intake estimates, reasons for discontinuing the step, and implications of its discontinuation. This step, termed salt adjustment, was performed in US Department of Agriculture (USDA) dietary intake surveys from 1985 through 2008. In What We Eat in America (WWEIA), the dietary intake interview component of the National Health and Nutrition Examination Survey (NHANES), the salt content of specific foods was reduced on the basis of a question about household use of salt in cooking. For individuals whose households used salt in cooking occasionally or less often, some or all of the salt attributable to home preparation was removed from foods that typically have salt added during preparation and were obtained from the store. The growing availability of preprepared foods in stores challenges the validity of using store purchase as a proxy indicator of home food preparation, and increased restaurant/fast-food consumption implies fewer reported foods are eligible for the procedure. In addition, USDAs Automated Multiple-Pass Method for the 24-hour dietary recall provides accurate sodium intake estimates without applying the salt-adjustment step. The final WWEIA, NHANES data release to contain salt-adjusted sodium data was 2007-2008. When assessing the effectiveness of sodium-reduction efforts over time, the nutrition community (eg, researchers, analysts, providers) must be aware of this change in WWEIA, NHANES beginning in 2009-2010 and account for it using appropriate baseline estimates.