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Background: Factor VIIc, fibrinogen, and plasminogen activator inhibitor 1 (PAI-1) are cardiovascular disease (CVD) risk factors and are modulated, in part, by fat type and amount., Objective: We evaluated fat type and amount on the primary outcomes: factor VIIc, fibrinogen, and PAI-1., Methods: In the Dietary Effects on Lipoproteins and Thrombogenic Activity (DELTA) Trial, 2 controlled crossover feeding studies evaluated substituting carbohydrate or MUFAs for SFAs. Study 1: healthy participants (n = 103) were provided with (8 wk) an average American diet [AAD; designed to provide 37% of energy (%E) as fat, 16% SFA], a Step 1 diet (30%E fat, 9% SFA), and a diet low in SFA (Low-Sat; 26%E fat, 5% SFA). Study 2: participants (n = 85) at risk for CVD and metabolic syndrome (MetSyn) were provided with (7 wk) an AAD, a step 1 diet, and a high-MUFA diet (designed to provide 37%E fat, 8% SFA, 22% MUFA)., Results: Study 1: compared with AAD, the Step 1 and Low-Sat diets decreased mean factor VIIc by 1.8% and 2.6% (overall P = 0.0001), increased mean fibrinogen by 1.2% and 2.8% (P = 0.0141), and increased mean square root PAI-1 by 0.0% and 6.0% (P = 0.0037), respectively. Study 2: compared with AAD, the Step 1 and high-MUFA diets decreased mean factor VIIc by 4.1% and 3.2% (overall P < 0.0001), increased mean fibrinogen by 3.9% and 1.5% (P = 0.0083), and increased mean square-root PAI-1 by 2.0% and 5.8% (P = 0.1319), respectively., Conclusions: Replacing SFA with carbohydrate decreased factor VIIc and increased fibrinogen in healthy and metabolically unhealthy individuals and also increased PAI-1 in healthy subjects. Replacing SFA with MUFA decreased factor VIIc and increased fibrinogen but less than carbohydrate. Our results indicate an uncertain effect of replacing SFA with carbohydrate or MUFA on cardiometabolic risk because of small changes in hemostatic factors and directionally different responses to decreasing SFA. This trial was registered at https://clinicaltrials.gov/ct2/show/NCT00000538?term=NCT00000538&rank=1 as NCT00000538., (Copyright © The Author(s) on behalf of the American Society for Nutrition 2020.)

Objective: This review summarizes the current and previous data on dietary supplement (DS) use collected from participants in the National Health and Nutrition Examination Survey (NHANES), describes the NHANES dietary supplement database used to compute nutrient intakes from DSs, discussed recent developments and future direction, and describes many examples to demonstrate the utility of these data in informing nutrition research and policy., Background and History: Since 1971, NHANES, has been collecting information on the use of DSs from participants. These data are critical to national nutrition surveillance and have been used to characterize usage patterns, examine trends over time, assess the percentage of the population meeting or exceeding nutrient recommendations, and to help elucidate the sources contributing nutrients to the diet of the US population., Rationale: Over half of adults and about one-third of children in the United States use at least one dietary supplement in the past 30 days. Dietary supplements contribute to the dietary intake of nutrients and bioactive compounds in the US and therefore need to be assessed when monitoring nutritional status of the population and when studying diet-health associations., Recent Developments: With the recent development and availability of the Dietary Supplement Label Database (DSLD), a comprehensive DS database that will eventually contain labels for all products marketed in the US, NHANES DS data will be more easily linked to product information to estimate nutrient intake from DS., Future Directions: Over time, NHANES has both expanded and improved collection methods. The continued understanding of sources of error in collection methods will continue to be explored and is critical to improved accuracy., Conclusions: NHANES provides a rich source of nationally representative data on the usage of dietary supplements in the US., Competing Interests: Conflicts of interest and funding disclosure: J. J. Gahche, R.L. Bailey, N. Potischman, A.G. Ershow, K.A. Herrick, N. Ahluwalia have no conflicts of interest. J.T. Dwyer has stock in several drug companies, some of which may sell dietary supplements. There is no funding to disclose.

Objective: To describe the history, key features, recent enhancements, and common applications of the Dietary Supplement Label Database (DSLD)., Background and History: Although many Americans use dietary supplements, databases of dietary supplements sold in the United States have not been widely available. The DSLD, an easily accessible public-use database was created in 2008 to provide information on dietary supplement composition for use by researchers and consumers., Rationale: Accessing current information easily and quickly is crucial for documenting exposures to dietary supplements because they contain nutrients and other bioactive ingredients that may have beneficial or adverse effects on human health. This manuscript details recent developments with the DSLD to achieve this goal and provides examples of how the DSLD has been used., Recent Developments: With periodic updates to track changes in product composition and capture new products entering the market, the DSLD currently contains more than 71,000 dietary supplement labels. Following usability testing with consumer and researcher user groups completed in 2016, improvements to the DSLD interface were made. As of 2017, both a desktop and mobile device version are now available. Since its inception in 2008, the use of the DSLD has included research, exposure monitoring, and other purposes by users in the public and private sectors., Future Directions: Further refinement of the user interface and search features to facilitate ease of use for stakeholders is planned., Conclusions: The DSLD can be used to track changes in product composition and capture new products entering the market. With over 71,000 DS labels it is a unique resource that policymakers, researchers, clinicians, and consumers may find valuable for multiple applications., Competing Interests: Conflicts of interest: JT Dwyer, RA Bailen, L Saldanha, J Gahche, R Costello, JM Betz, Cindy Davis, RL Bailey, N Potischman, A Ershow, B Sorkin, A Kuszak,L Rios-Avila, F Chang, J Goshorn, K Andrews, P Pehrsson, P Gusev, J Harnly, CJ Hardy, N Emenaker, KA Herrick, no conflicts of interest.

Launched in 2008, the Dietary Supplement Label Database (DSLD) permits the search of any term that appears anywhere on product labels. Since then, the database's search and download features have been periodically improved to enhance use for researchers and consumers. In this review, we describe how to customize searches and identify products and ingredients of interest to users in the DSLD, and provide the limitations of working with information derived from dietary supplement product labels. This article describes how data derived from information printed on product labels are entered and organized in the DSLD. Among the challenges are determining the chemical forms, types of extract, and amounts of dietary ingredients, especially when these are components of proprietary blends. The FDA announced new dietary supplement labeling regulations in May 2016. The 2017 DSLD has been updated to reflect them. These new regulations and examples cited in this article refer to this redesigned version of the DSLD. Search selection characteristics such as for product type and intended user group are as described in FDA guidance and regulations for dietary supplements. For this reason, some age groups (such as teens and seniors) and marketing recommendations for use (e.g., weight loss, performance, and other disease- or condition-specific claims) are not included in the search selections. The DSLD user interface features will be revised periodically to reflect regulatory and technologic developments to enhance user experience. A comprehensive database derived from analytically verified data on composition would be preferable to label data, but is not feasible for technical, logistic, and financial reasons. Therefore, a database derived from information printed on product labels is the only practical option at present for researchers, clinicians, and consumers interested in the composition of these products., (© Crown copyright 2018.)