Fortification: new findings and implications

This article reviews the current landscape regarding food fortification in the United States; the content is based on aworkshop sponsored by the North American Branch of the International Life Sciences Institute. Fortification of the food supply with vitamins and minerals is a public health strategy to enhance nutrient intakes of the population without increasing caloric intake. Many individuals in the United States would not achieve recommended micronutrient intakes without fortification of the food supply. The achievement and maintenance of a desirable level of nutritional quality in the nation\u27s food supply is, thus, an important public health objective. While the addition of nutrients to foods can help maintain and improve the overall nutritional quality of diets, indiscriminate fortification of foods could result in overfortification or underfortification in the food supply and nutrient imbalances in the diets of individuals. Any changes in food fortification policy for micronutrients must be considered within the context of the impact they will have on all segments of the population and of food technology and safety applications and their limitations. This article discusses and evaluates the value of fortification, the success of current fortification efforts, and the future role of fortification in preventing or reversing nutrient inadequacies

USDA Food and Nutrient Database for Dietary Studies (FNDDS), 5.0

AbstractThe Food and Nutrient Database for Dietary Studies (FNDDS) is used to code and analyze dietary intakes for the What We Eat In America, National Health and Nutrition Examination Survey (WWEIA, NHANES). To create FNDDS 5.0 for WWEIA, NHANES 2009-2010, data for over 7,200 foods were updated to incorporate changes in the marketplace and information reported by survey participants. The updates include nearly 100 new foods and extensive changes to food descriptions, portions, weights, and recipes. The USDA National Nutrient Database for Standard Reference, Release 24 is the basis for the 65 nutrient values for each FNDDS food. FNDDS 5.0 is available at http://www.ars.usda.gov/ba/bhnrc/fsrg

Cross-continental comparison of national food consumption survey methods—A narrative review

Food consumption surveys are performed in many countries. Comparison of results from those surveys across nations is difficult because of differences in methodological approaches. While consensus about the preferred methodology associated with national food consumption surveys is increasing, no inventory of methodological aspects across continents is available. The aims of the present review are (1) to develop a framework of key methodological elements related to national food consumption surveys, (2) to create an inventory of these properties of surveys performed in the continents North- America, South-America, Asia and Australasia, and (3) to discuss and compare these methodological properties cross-continentally. A literature search was performed using a fixed set of search terms in different databases. The inventory was completed with all accessible information from all retrieved publications and corresponding authors were requested to provide additional information where missing. Surveys from ten individual countries, originating from four continents are listed in the inventory. The results are presented according to six major aspects of food consumption surveys. The most common dietary intake assessment method used in food consumption surveys worldwide is the 24-HDR (24 h dietary recall), occasionally administered repeatedly, mostly using interview software. Only three countries have incorporated their national food consumption surveys into continuous national health and nutrition examination surveys

Comparison of two different physical activity monitors

<p>Abstract</p> <p>Background</p> <p>Understanding the relationships between physical activity (PA) and disease has become a major area of research interest. Activity monitors, devices that quantify free-living PA for prolonged periods of time (days or weeks), are increasingly being used to estimate PA. A range of different activity monitors brands are available for investigators to use, but little is known about how they respond to different levels of PA in the field, nor if data conversion between brands is possible.</p> <p>Methods</p> <p>56 women and men were fitted with two different activity monitors, the Actigraph™ (Actigraph LLC; AGR) and the Actical™ (Mini-Mitter Co.; MM) for 15 days. Both activity monitors were fixed to an elasticized belt worn over the hip, with the anterior and posterior position of the activity monitors randomized. Differences between activity monitors and the validity of brand inter-conversion were measured by <it>t</it>-tests, Pearson correlations, Bland-Altman plots, and coefficients of variation (CV).</p> <p>Results</p> <p>The AGR detected a significantly greater amount of daily PA (216.2 ± 106.2 vs. 188.0 ± 101.1 counts/min, P < 0.0001). The average difference between activity monitors expressed as a CV were 3.1 and 15.5% for log-transformed and raw data, respectively. When a conversion equation was applied to convert datasets from one brand to another, the differences were no longer significant, with CV's of 2.2 and 11.7%, log-transformed and raw data, respectively.</p> <p>Conclusion</p> <p>Although activity monitors predict PA on the same scale (counts/min), the results between these two brands are not directly comparable. However, the data are comparable if a conversion equation is applied, with better results for log-transformed data.</p

Sodium and potassium intakes among US adults: NHANES 2003–2008

Background: The American Heart Association (AHA), Institute of Medicine (IOM), and US Departments of Health and Human Services and Agriculture (USDA) Dietary Guidelines for Americans all recommend that Americans limit sodium intake and choose foods that contain potassium to decrease the risk of hypertension and other adverse health outcomes. Objective: We estimated the distributions of usual daily sodium and potassium intakes by sociodemographic and health characteristics relative to current recommendations. Design: We used 24-h dietary recalls and other data from 12,581 adults aged $20 y who participated in NHANES in 2003–2008. Estimates of sodium and potassium intakes were adjusted for withinindividual day-to-day variation by using measurement error models. SEs and 95$51 y or persons with hypertension, diabetes, or chronic kidney disease), 98.8% (98.4%, 99.2%) overall consumed .1500 mg/d, and 60.4% consumed .3000 mg/d—more than double the recommendation. Overall, ,2% of US adults and w5% of US men consumed $4700 mg K/d (ie, met recommendations for potassium). Conclusion: Regardless of recommendations or sociodemographic or health characteristics, the vast majority of US adults consume too much sodium and too little potassium

Estimates of adherence and error analysis of physical activity data collected via accelerometry in a large study of free-living adults

<p>Abstract</p> <p>Background</p> <p>Activity monitors (AM) are small, electronic devices used to quantify the amount and intensity of physical activity (PA). Unfortunately, it has been demonstrated that data loss that occurs when AMs are not worn by subjects (removals during sleeping and waking hours) tend to result in biased estimates of PA and total energy expenditure (TEE). No study has reported the degree of data loss in a large study of adults, and/or the degree to which the estimates of PA and TEE are affected. Also, no study in adults has proposed a methodology to minimize the effects of AM removals.</p> <p>Methods</p> <p>Adherence estimates were generated from a pool of 524 women and men that wore AMs for 13 – 15 consecutive days. To simulate the effect of data loss due to AM removal, a reference dataset was first compiled from a subset consisting of 35 highly adherent subjects (24 HR; minimum of 20 hrs/day for seven consecutive days). AM removals were then simulated during sleep and between one and ten waking hours using this 24 HR dataset. Differences in the mean values for PA and TEE between the 24 HR reference dataset and the different simulations were compared using paired <it>t</it>-tests and/or coefficients of variation.</p> <p>Results</p> <p>The estimated average adherence of the pool of 524 subjects was 15.8 ± 3.4 hrs/day for approximately 11.7 ± 2.0 days. Simulated data loss due to AM removals during sleeping hours in the 24 HR database (n = 35), resulted in biased estimates of PA (p < 0.05), but not TEE. Losing as little as one hour of data from the 24 HR dataset during waking hours results in significant biases (p < 0.0001) and variability (coefficients of variation between 7 and 21%) in the estimates of PA. Inserting a constant value for sleep and imputing estimates for missing data during waking hours significantly improved the estimates of PA.</p> <p>Conclusion</p> <p>Although estimated adherence was good, measurements of PA can be improved by relatively simple imputation of missing AM data.</p

The Third Step—The National “What We Eat in America” Survey

In 2010, landmark health legislation— the Affordable Care Act—was passed, leading to a national strategy crossing both private and public sectors and led by the National Prevention, Health Promotion, and Public Health Council of the Surgeon General. The plan is called the “National Prevention Strategy.” Science-based dietary-intake data from the Agricultural Research Service provides a key foundation for multiple public health policy publications, including the council’s strategy report, published in June 2011. The report cites the ARS national dietary-intake survey data to underscore the ability of everyday people to improve their health through healthy eating and other preventive measures. Collecting data on what we eat in America is a key monitoring step that connects what Americans eat to their nutrition and health status and to health outcomes. Research nutritionists work on translating “foods eaten” into “nutrients consumed” to get a snapshot of the population’s nutrient intake status. The dietary-intake survey data—after analysis—helps inform major nutrition policy, such as food fortification regulations, nutrition education, food assistance and safety programs, and various dietary guidelines

Dietary Flavonoid Intake Is Inversely Associated with Cardiovascular Disease Risk as Assessed by Body Mass Index and Waist Circumference among Adults in the United States

Although flavonoids may confer anti-inflammatory and anti-oxidant benefits, no research has examined if flavonoid intake is related to cardiovascular disease (CVD) risk defined by anthropometric measures in the USA population. This study sought to determine whether flavonoid intake is associated with combined body mass index (BMI) and waist circumference (WC) measures indicative of high, very high, or extremely high (“high+”) risk for CVD, using one day of 24-h recall data from adult (≥20 years) participants in What We Eat in America, National Health and Nutrition Examination Survey 2007–2010. Individuals were divided into categories of intake of total flavonoids and each flavonoid class, and adjusted estimates of the percentages at high+ CVD risk (based on BMI and WC, as per National Heart, Lung, and Blood Institute guidelines) were calculated. Inverse linear trends were found in percentages of adults at high+ CVD risk by intake of total flavonoids, anthocyanidins, flavan-3-ols, and flavanones (p &lt; 0.01). For individuals in the highest (versus the lowest) intake category of anthocyanidins, flavan-3-ols, and flavanones, relative risk and confidence intervals (RR and CI, respectively) were 0.86 (99% CI: 0.79, 0.93), 0.88 (99% CI: 0.79, 0.98), and 0.89 (99% CI: 0.80, 0.98), respectively. Research is needed to determine whether the inverse relationships found in this study are applicable to CVD endpoints at the population level