What We Eat in America (WWEIA) is the dietary intake interview component of the National Health and Nutrition Examination Survey (NHANES). WWEIA is conducted as a partnership between the U.S. Department of Agriculture (USDA) and the U.S. Department of Health and Human Services (DHHS). Two days of 24-hour dietary recall data are collected through an initial in-person interview, and a second interview conducted over the telephone within three to 10 days. Participants are given three-dimensional models (measuring cups and spoons, a ruler, and two household spoons) and/or USDA's Food Model Booklet (containing drawings of various sizes of glasses, mugs, bowls, mounds, circles, and other measures) to estimate food amounts. WWEIA data are collected using USDA's dietary data collection instrument, the Automated Multiple-Pass Method (AMPM). The AMPM is a fully computerized method for collecting 24-hour dietary recalls either in-person or by telephone. For each 2-year data release cycle, the following dietary intake data files are available: Individual Foods File - Contains one record per food for each survey participant. Foods are identified by USDA food codes. Each record contains information about when and where the food was consumed, whether the food was eaten in combination with other foods, amount eaten, and amounts of nutrients provided by the food. Total Nutrient Intakes File - Contains one record per day for each survey participant. Each record contains daily totals of food energy and nutrient intakes, daily intake of water, intake day of week, total number foods reported, and whether intake was usual, much more than usual or much less than usual. The Day 1 file also includes salt use in cooking and at the table; whether on a diet to lose weight or for other health-related reason and type of diet; and frequency of fish and shellfish consumption (examinees one year or older, Day 1 file only). DHHS is responsible for the sample design and data collection, and USDA is responsible for the survey’s dietary data collection methodology, maintenance of the databases used to code and process the data, and data review and processing. USDA also funds the collection and processing of Day 2 dietary intake data, which are used to develop variance estimates and calculate usual nutrient intakes. Resources in this dataset:Resource Title: What We Eat In America (WWEIA) main web page. File Name: Web Page, url: https://www.ars.usda.gov/northeast-area/beltsville-md-bhnrc/beltsville-human-nutrition-research-center/food-surveys-research-group/docs/wweianhanes-overview/ Contains data tables, research articles, documentation data sets and more information about the WWEIA program. (Link updated 05/13/2020)

The dataset, Survey-SR, provides the nutrient data for assessing dietary intakes from the national survey What We Eat In America, National Health and Nutrition Examination Survey (WWEIA, NHANES). Historically, USDA databases have been used for national nutrition monitoring (1). Currently, the Food and Nutrient Database for Dietary Studies (FNDDS) (2), is used by Food Surveys Research Group, ARS, to process dietary intake data from WWEIA, NHANES. Nutrient values for FNDDS are based on Survey-SR. Survey-SR was referred to as the "Primary Data Set" in older publications. Early versions of the dataset were composed mainly of commodity-type items such as wheat flour, sugar, milk, etc. However, with increased consumption of commercial processed and restaurant foods and changes in how national nutrition monitoring data are used (1), many commercial processed and restaurant items have been added to Survey-SR. The current version, Survey-SR 2013-2014, is mainly based on the USDA National Nutrient Database for Standard Reference (SR) 28 (2) and contains sixty-six nutrientseach for 3,404 foods. These nutrient data will be used for assessing intake data from WWEIA, NHANES 2013-2014. Nutrient profiles were added for 265 new foods and updated for about 500 foods from the version used for the previous survey (WWEIA, NHANES 2011-12). New foods added include mainly commercially processed foods such as several gluten-free products, milk substitutes, sauces and condiments such as sriracha, pesto and wasabi, Greek yogurt, breakfast cereals, low-sodium meat products, whole grain pastas and baked products, and several beverages including bottled tea and coffee, coconut water, malt beverages, hard cider, fruit-flavored drinks, fortified fruit juices and fruit and/or vegetable smoothies. Several school lunch pizzas and chicken products, fast-food sandwiches, and new beef cuts were also added, as they are now reported more frequently by survey respondents. Nutrient profiles were updated for several commonly consumed foods such as cheddar, mozzarella and American cheese, ground beef, butter, and catsup. The changes in nutrient values may be due to reformulations in products, changes in the market shares of brands, or more accurate data. Examples of more accurate data include analytical data, market share data, and data from a nationally representative sample. Resources in this dataset:Resource Title: USDA National Nutrient Database for Standard Reference Dataset for What We Eat In America, NHANES 2013-14 (Survey SR 2013-14). File Name: SurveySR_2013_14 (1).zipResource Description: Access database downloaded on November 16, 2017. US Department of Agriculture, Agricultural Research Service, Nutrient Data Laboratory. USDA National Nutrient Database for Standard Reference Dataset for What We Eat In America, NHANES (Survey-SR), October 2015. Resource Title: Data Dictionary. File Name: SurveySR_DD.pdf

[Note: Integrated as part of FoodData Central, April 2019.] USDA's Food and Nutrient Database for Dietary Studies (FNDDS) is a database that is used to convert food and beverages consumed in What We Eat In America (WWEIA), National Health and Nutrition Examination Survey (NHANES) into gram amounts and to determine their nutrient values. Because FNDDS is used to generate the nutrient intake data files for WWEIA, NHANES, it is not required to estimate nutrient intakes from the survey. FNDDS is made available for researchers using WWEIA, NHANES to review the nutrient profiles for specific foods and beverages as well as their associated portions and recipes. Such detailed information makes it possible for researchers to conduct enhanced analysis of dietary intakes. FNDDS can also be used in other dietary studies to code foods/beverages and amounts eaten and to calculate the amounts of nutrients/food components in those items.
FNDDS is released every two-years in conjunction with the WWEIA, NHANES dietary data release. The FNDDS is available for free download from the FSRG website. Resources in this dataset:Resource Title: Website Pointer to Food and Nutrient Database for Dietary Studies. File Name: Web Page, url: https://www.ars.usda.gov/northeast-area/beltsville-md-bhnrc/beltsville-human-nutrition-research-center/food-surveys-research-group/docs/fndds/ USDA's Food and Nutrient Database for Dietary Studies (FNDDS) is a database that is used to convert food and beverages consumed in What We Eat In America (WWEIA), National Health and Nutrition Examination Survey (NHANES) into gram amounts and to determine their nutrient values.

The Nutrient Data Laboratory is responsible for developing authoritative nutrient databases that contain a wide range of food composition values of the nation's food supply. This requires updating and revising the USDA Nutrient Database for Standard Reference (SR) and developing various special interest databases. However, with over 7,000 food items in SR and a complete nutrient profile costing approximately $2,000 for one sample, analyzing every food item for every nutrient and meeting all user requirements is impossible. Consequently, priorities must be determined. Procedures using food consumption data and nutrient values for developing the Key Foods list are explained. Key Foods have been identified as those food items that contribute up to 75% of any one nutrient to the dietary intake of the US population. These Key Foods will be used to set priorities for nutrient analyses under the National Food and Nutrient Analysis Program. The tables describe key foods based on Continuing Survey Of Food Intakes By Individuals (CSFII, 1989-) and WWEIA-NHANES (What We Eat In America - National Health and Nutrition Examination Survey 2001-) survey data. Resources in this dataset:Resource Title: List of Key Foods based on CSFII 1989-91. File Name: KeyFoods_key_ls91.txtResource Description: Key Foods based on CSFII 1989-91 https://www.ars.usda.gov/ARSUserFiles/80400525/Data/KeyFoods/key_ls91.txtResource Title: List of Key Foods based on CSFII 1994-96 . File Name: KeyFoods_key_ls9496.txtResource Description: List of Key Foods based on CSFII 1994-96 https://www.ars.usda.gov/ARSUserFiles/80400525/Data/KeyFoods/key_ls9496.txtResource Title: List of Key Foods based on WWEIA-NHANES 2001-02. File Name: KeyFoods_key_ls0102.txtResource Description: List of Key Foods based on WWEIA-NHANES 2001-02 https://www.ars.usda.gov/ARSUserFiles/80400525/Data/KeyFoods/key_ls0102.txtResource Title: List of Key Foods based on WWEIA-NHANES 2003-04 . File Name: KeyFoods_key_ls0304.txtResource Description: https://www.ars.usda.gov/ARSUserFiles/80400525/Data/KeyFoods/key_ls0304.txtResource Title: List of Key Foods based on WWEIA-NHANES 2007-08. File Name: Keyfoods_0708.xlsxResource Description: List of Key Foods based on WWEIA-NHANES 2007-08 https://www.ars.usda.gov/ARSUserFiles/80400525/Data/KeyFoods/Keyfoods_0708.xlsxResource Title: List of Key Foods based on WWEIA-NHANES 2009-10. File Name: Keyfoods_0910.xlsxResource Description: List of Key Foods based on WWEIA-NHANES 2009-10 https://www.ars.usda.gov/ARSUserFiles/80400525/Data/KeyFoods/Keyfoods_0910.xlsxResource Title: List of Key Foodsbased on WWEIA-NHANES 2011-12. File Name: Keyfoods_1112.xlsxResource Description: List of Key Foodsbased on WWEIA-NHANES 2011-12 https://www.ars.usda.gov/ARSUserFiles/80400525/Data/KeyFoods/Keyfoods_1112.xlsx

Computational models have gained popularity as a predictive tool for assessing proposed policy changes affecting dietary choice. Specifically, they have been used for modeling dietary changes in response to economic interventions, such as price and income changes. Herein, we present a novel addition to this type of model by incorporating habitual behaviors that drive individuals to maintain or conform to prior eating patterns. We examine our method in a simulated case study of food choice behaviors of low-income adults in the US. We use data from several national datasets, including the National Health and Nutrition Examination Survey (NHANES), the US Bureau of Labor Statistics and the USDA, to parameterize our model and develop predictive capabilities in 1) quantifying the influence of prior diet preferences when food budgets are increased and 2) simulating the income elasticities of demand for four food categories. Food budgets can increase because of greater affordability (due to food aid and other nutritional assistance programs), or because of higher income. Our model predictions indicate that low-income adults consume unhealthy diets when they have highly constrained budgets, but that even after budget constraints are relaxed, these unhealthy eating behaviors are maintained. Specifically, diets in this population, before and after changes in food budgets, are characterized by relatively low consumption of fruits and vegetables and high consumption of fat. The model results for income elasticities also show almost no change in consumption of fruit and fat in response to changes in income, which is in agreement with data from the World Bank’s International Comparison Program (ICP). Hence, the proposed method can be used in assessing the influences of habitual dietary patterns on the effectiveness of food policies.

Improving diet quality while simultaneously reducing environmental impact is a critical focus globally. Metrics linking diet quality and sustainability have typically focused on a limited suite of indicators, and have not included food waste. To address this important research gap, we examine the relationship between food waste, diet quality, nutrient waste, and multiple measures of sustainability: use of cropland, irrigation water, pesticides, and fertilizers. Data on food intake, food waste, and application rates of agricultural amendments were collected from diverse US government sources. Diet quality was assessed using the Healthy Eating Index-2015. A biophysical simulation model was used to estimate the amount of cropland associated with wasted food. This analysis finds that US consumers wasted 422g of food per person daily, with 30 million acres of cropland used to produce this food every year. This accounts for 30% of daily calories available for consumption, one-quarter of daily food (by weight) available for consumption, and 7% of annual cropland acreage. Higher quality diets were associated with greater amounts of food waste and greater amounts of wasted irrigation water and pesticides, but less cropland waste. This is largely due to fruits and vegetables, which are health-promoting and require small amounts of cropland, but require substantial amounts of agricultural inputs. These results suggest that simultaneous efforts to improve diet quality and reduce food waste are necessary.. Increasing consumers’ knowledge about how to prepare and store fruits and vegetables will be one of the practical solutions to reducing food waste. Relationship between food waste, diet quality, and environmental sustainability

ObjectivesWhile it is widely perceived that the diet consumed by Japanese is healthy, empirical evidence supporting this notion is limited. In this cross-sectional study, we assessed the overall diet quality of Japanese using the Healthy Eating Index-2015 (HEI-2015) and Nutrient-Rich Food Index 9.3 (NRF9.3), and compared diet quality scores between Japanese and Americans.MethodsWe used 1-d dietary record data from 19,719 adults (aged ≥20 y) in the Japanese National Health and Nutrition Survey 2012 and the first 24-h dietary recall data from 4614 adults in the US NHANES 2011–2012.ResultsAs expected, a higher total score of the HEI-2015 and NRF9.3 was associated with favorable patterns of overall diet in the Japanese population. The range of total score was wide enough for both HEI-2015 (5th percentile 37.2; 95th percentile 67.2) and NRF9.3 (5th percentile 257; 95th percentile 645). Both HEI-2015 and NRF9.3 distinguished known differences in diet quality between sex, age, and smoking status. The mean total scores of HEI-2015 and NRF9.3 were similar between Japanese (51.9 and 448, respectively) and US adults (52.8 and 435, respectively). However, component scores between the 2 populations were considerably different. For HEI-2015, Japanese had higher scores for whole fruits, total vegetables, green and beans, total protein foods, seafood and plant proteins, fatty acids, added sugars, and saturated fats, but lower scores for total fruits, whole grains, dairy, refined grains, and sodium. For NRF9.3, the intakes of vitamin C, vitamin D, potassium, added sugars, and saturated fats were more favorable in Japanese, while those of dietary fiber, vitamin A, calcium, iron, magnesium, and sodium were less favorable.ConclusionsThis study suggests the usefulness of HEI-2015 and NRF9.3 for assessing the diet quality of Japanese, as well as for highlighting different nutritional concerns between Japan and the US.

Several studies indicate that the four major types of resistant starch (RS1-4) are fermented in the cecum and colon to produce short-chain fatty acids (SCFAs) and can alter the microbiome and host physiology. However, nearly all these studies were conducted in rodents fed with a diet that does not approximate what is typically consumed by humans. To address this, mice were fed a Total Western Diet (TWD) based on National Health and Nutrition Examination Survey (NHANES) data that mimics the macro and micronutrient composition of a typical American diet for 6 weeks and then supplemented with 0, 2, 5, or 10% of the RS2, resistant potato starch (RPS), for an additional 3 weeks. The cecal microbiome was analyzed by 16S sequencing. The alpha-diversity of the microbiome decreased with increasing consumption of RPS while a beta-diversity plot showed four discreet groupings based on the RPS level in the diet. The relative abundance of various genera was altered by feeding increasing levels of RPS. In particular, the genus Lachnospiraceae NK4A136 group was markedly increased. Cecal, proximal, and distal colon tissue mRNA abundance was analyzed by RNASeq. The cecal mRNA abundance principal component analysis showed clear segregation of the four dietary groups whose separation decreased in the proximal and distal colon. Differential expression of the genes was highest in the cecum, but substantially decreased in the proximal colon (PC) and distal colon (DC). Most differentially expressed genes were unique to each tissue with little overlap in between. The pattern of the observed gene expression suggests that RPS, likely through metabolic changes secondary to differences in microbial composition, appears to prime the host to respond to a range of pathogens, including viruses, bacteria, and parasites. In summary, consumption of dietary RPS led to significant changes to the microbiome and gene expression in the cecum and to a lesser extent in the proximal and distal colon.

After decades-old efforts to nudge consumers towards healthier lifestyles through dietary guidelines, diet-related diseases are on the rise. In addition, a growing share of U.S. consumers proactively chooses nutritional supplements as an alternative preventative way of maintaining good health, a $25.5 billion industry in the United States. This paper investigates possible linkages between the economics of consumer supplement choices and the relationship to important dietary and health outcomes. We use National Health and Nutrition Examination Survey (NHANES) data to estimate the impact of nutritional supplements intake on respondent’s body weight outcomes, controlling for diet quality.: The focus of this article is to determine whether nutritional supplements takers differ from non-takers with regard to their health outcomes when controlling for differences in diet quality, based on individual Healthy Eating Index (HEI-2010) score. The analysis applies treatment effects estimators that account for the selection bias and endogeneity of self-reported behavior and diet-health outcomes. The analysis demonstrates a negative association between supplement intake and BMI but no significant effect on an individual’s diet quality. Our findings suggest that individuals proactively invest into their health by taking nutritional supplements instead of improving diet quality through more nutritious food choices. Our results provide important contributions to the literature on a key food policy issue. Knowledge of the determinants of supplement demand in the context of strong diet-health trends should also be helpful to stakeholders in the U.S. produce sector in their competition over consumer market share.

ObjectivesTo examine national trends in unhealthy lifestyle factors among adults with cardiovascular disease (CVD) in the United States (US) between 1999 and 2018.MethodsWe analyzed data from National Health and Nutrition Examination Survey (NHANES), a nationally representative survey of participants with CVD who were aged ≥20 years, which was conducted between 1999 and 2000 and 2017–2018. CVD was defined as a self-report of congestive heart failure, coronary heart disease, angina, heart attack, or stroke. The prevalence rate of each unhealthy lifestyle factor was calculated among adults with CVD for each of the 2-year cycle surveys. Regression analyses were used to assess the impact of sociodemographic characteristics (age, sex, race/ethnicity, family income, education level, marital status, and employment status).ResultsThe final sample included 5610 NHANES respondents with CVD. The prevalence rate of their current smoking status remained stable among respondents with CVD between 1999 and 2000 and 2017–2018. During the same period, there was a decreasing trend in the age-adjusted prevalence rate of poor diet [primary American Heart Association (AHA) score <20; 47.5% (37.9%–57.0%) to 37.5% (25.7%–49.3%), p < 0.01]. Physical inactivity marginally increased before decreasing, with no statistical significance. The prevalence rate of sedentary behavior increased from 2007 to 2014 but subsequently returned to its original level in 2018 with no statistical significance. The age-adjusted prevalence rate of obesity increased from 32% (27.2%–36.8%) in 1999–2000 to 47.9% (39.9%–55.8%) in 2017–2018 (p < 0.001). The age-adjusted prevalence rate of depression increased from 7% (4.2%–9.9%) in 1999–2000 to 13.9% (10.2%–17.6%) in 2017–2018 (p = 0.056). Trends in mean for each unhealthy lifestyle factor were similar after adjustment for age. We found that respondents who had low education and income levels were at a higher risk of being exposed to unhealthy lifestyle factors (i.e., smoking, poor diet, and physical inactivity) than those who had high education and income levels.ConclusionsThere is a significant reduction in the prevalence rate of poor diet among US adults with CVD between 1999 and 2018, while the prevalence rate of obesity showed increasing trends over this period. The prevalence rate of current smoking status, sedentary behavior, and depression was either stable or showed an insignificant increase. These findings suggest that there is an urgent need for health policy interventions targeting unhealthy lifestyles among adults with CVD.

Recent estimates of added sugars intake among the U.S. population show intakes are above recommended levels. Knowledge about the sources of added sugars contributing to intakes is required to inform dietary guidance, and understanding how those sources vary across sociodemographic subgroups could also help to target guidance. The purpose of this study was to provide a comprehensive update on sources of added sugars among the U.S. population, and to examine variations in sources according to sociodemographic factors. Regression analyses on intake data from NHANES 2011–18 were used to examine sources of added sugars intake among the full sample (N = 30,678) and among subsamples stratified by age, gender, ethnicity, and income. Results showed the majority of added sugars in the diet (61–66%) came from a few sources, and the top two sources were sweetened beverages and sweet bakery products, regardless of age, ethnicity, or income. Sweetened beverages, including soft drinks and fruit drinks, as well as tea, were the largest contributors to added sugars intake. There were some age-, ethnic-, and income-related differences in the relative contributions of added sugars sources, highlighting the need to consider sociodemographic contexts when developing dietary guidance or other supports for healthy eating.

BackgroundThe Planetary Health Diet (PHD) is a novel dietary pattern proposed by the EAT-Lancet Commission in 2019, yet a limited study has investigated the anti-aging effects of PHD to date.ObjectivesThis study aimed to explore the association between adherence to PHD, as quantified by the Planetary Health Diet Index (PHDI), and biological aging in American populations.MethodsData were obtained from the National Health and Nutrition Examination Survey (NHANES) for 1999–2018. Food consumption information was relied on two 24-h diet recall questionnaires. The biological aging condition was comprehensively assessed by four biological markers, including phenotypic age, biological age, telomere length, and klotho concentration. Weighted multivariate linear models, restricted cubic spline (RCS), and subgroup analysis were subsequently carried out to evaluate the influence of PHDI on biological aging.Results44,925 participants with complete data were finally enrolled in our study. The fully adjusted models showed decreased 0.20 years in phenotypic age [−0.20 (−0.31, −0.10)] and declined 0.54 years in biological age [−0.54 (−0.69, −0.38)] correlated with PHDI per 10 scores increment. Klotho concentration [6.2 (1.0, 11.0)] was positively related to PHDI. In Model 2, telomere length increased by 0.02 bp for every 10-point rise in PHDI. Besides, the RCS analysis results exhibited a curvilinear relationship between PHDI and four indicators.ConclusionOur study explored a significant correlation between PHDI and biological aging, indicating that adherence to PHD may prevent biological aging.

BackgroundMaternal nutrition is critical to the health of both mother and offspring, but there is a paucity of data on the nutritional adequacy of diets during pregnancy.ObjectiveOur objective was to identify to what extent pregnancy reduces the nutritional adequacy of the expecting mother’s diet and if this nutritional gap can be resolved by simple quantitative or qualitative changes in the diet.Materials and MethodsWe evaluated the observed overall nutritional adequacy of diets of French and American women of childbearing age participating in ENNS (n = 344) and NHANES (n = 563) using the probabilistic approach of the PANDiet system, resulting in a 100-point score. Then, we simulated the changes in the PANDiet scores of women of childbearing age who would remain on their diet during pregnancy. Finally, by either increasing the quantity of consumed foods or using eleven snacks recommended during pregnancy, we simulated the effect of a 150-kcal increase in the energy intake of French women.ResultsObserved PANDiet scores were equal to 59.3 ± 7.0 and 58.8 ± 9.3 points respectively in France and in the US. Simulation of pregnancy for women of childbearing age led to a decrease in nutritional adequacy for key nutrients during pregnancy and resulted in reducing PANDiet scores by 3.3 ± 0.1 and 3.7 ± 0.1 points in France and in the US. Simulated 150-kcal increases in energy intake proved to be only partially effective in filling the gap both when the quantity of food consumed was increased and when recommended snacks were used.ConclusionsThe decrease in nutritional adequacy induced by pregnancy cannot be addressed by simply following generic dietary guidelines.

BackgroundRespiratory health is closely related to immune system function, and diet can also influence immune homeostasis. Diet, an important part of a healthy lifestyle, is also linked to respiratory health. We aimed to explore the relationship between different dietary patterns and the risk of chronic respiratory diseases (CRDs), including chronic bronchitis (CB), emphysema, and asthma.MethodA total of 23,042 adults from the United States were selected from the National Health and Nutrition Examination Survey (NHANES) dataset between 2007 and 2018. Diet quality was assessed using 2-day, 24-hour dietary recall data and quantified as the Healthy Eating Index-2020 (HEI-2020), the Dietary Inflammation Index (DII), the Mediterranean Dietary Index (MEDI), and the Dietary Approaches to Stop Hypertension Index (DASHI). Binary logistic regression models, restricted cubic splines (RCS), and the weighted quartile sum (WQS) models were used to assess the relationship between diet quality and the risk of CB, emphysema, and asthma.ResultsIn logistic regression analyses of the four dietary indices with the three chronic respiratory diseases, it was consistently observed that higher dietary quality scores were linked to a reduced risk of respiratory disease. These consistent trends were also evident in the assessments of the dose–response relationship between dietary quality score and the risk of respiratory disease. Furthermore, evaluations of the combined effects of dietary components across different dietary indices in the risk of chronic respiratory disease yielded results consistent with the logistic regression models. Notably, high-quality protein, minerals, and fiber-rich fruits and vegetables emerged as the food groups making the most significant contributions to health across different dietary indices.ConclusionLow-quality diets, lacking in high-quality protein, minerals, and fruits and vegetables rich in dietary fiber, are associated with a higher risk of chronic respiratory disease, regardless of the dietary index used to measure diet quality.

BackgroundThe Dietary Approaches to Stop Hypertension (DASH) and the Mediterranean diet are associated with reduced cardiovascular, tumor, and diabetes risk, but the effect on chronic obstructive pulmonary disease (COPD) is uncertain.ObjectiveTo investigate the association of the DASH diet and the Mediterranean diet with the risk of COPD in American adults.MethodsThis cross-sectional study included 28,605 participants from the National Health and Nutrition Examination Survey (NHANES) 1999–2018 survey cycle who had complete dietary and other questionnaire data. The scores of healthy eating patterns (the DASH diet and the Mediterranean diet) were derived from a 24-h dietary recall interview [individual food and total nutrient data from NHANES and food pattern equivalents data from the United States Department of Agriculture (USDA)]. The primary outcome was the prevalence of COPD. COPD was defined based on participants self-reported whether or not a doctor or health professional had diagnosed chronic bronchitis or emphysema. Secondary outcomes were lung function and respiratory symptoms. All analyses were adjusted for demographics and standard COPD risk factors (primary tobacco exposure, secondhand smoke exposure, and asthma).ResultsThis study included 2,488 COPD participants and 25,607 non-COPD participants. We found that a higher DASH diet score was associated with a lower risk of COPD [odds ratio (OR): 0.83; 95% confidence interval (CI): 0.71–0.97; P = 0.021]. This association persisted in several subgroups [men (OR: 0.73; 95% CI: 0.58–0.93; P = 0.010), relatively young (OR: 0.74; 95% CI: 0.55–1.01; P = 0.050), and smoker (OR: 0.82; 95% CI: 0.67–0.99; P = 0.038)]. In contrast, the Mediterranean diet score was not significantly associated with COPD prevalence in this large cross-sectional analysis representative of the US adult population (OR: 1.03; 95% CI: 0.88–1.20; P = 0.697). In addition, we found a correlation between DASH diet adherence and lung function [β: −0.01; 95% CI: −0.01–0.00; P = 0.003 (FEV1: FVC)] or respiratory symptoms [OR: 0.80; 95% CI: 0.73–0.89; P < 0.001 (dyspnea); OR: 0.80; 95% CI: 0.70–0.91; P = 0.002 (cough); OR: 0.86; 95% CI: 0.74–0.99; P = 0.042 (expectoration)], especially in non-COPD populations.ConclusionA higher DASH diet score was associated with improved COPD prevalence, lung function and respiratory symptoms. This new finding supports the importance of diet in the pathogenesis of COPD and expands the scope of the association of the DASH diet score with major chronic diseases.

Demographic, socioeconomic characteristics across cooking frequency categories among Non-Hispanic Black (NHB) adults, U.S. NHANES, 2007–2010.

Diet related NCD deaths that could be averted or delayed in the US due to changes in calorie and nutrients-of-concern content in food and beverage purchases in the presence of nutrient-specific ‘high in’ FOPL.

BackgroundA shift toward more sustainable diets, rich in plant-based foods and with fewer animal-derived foods, is needed and will lead to improved health and environmental benefits. Food industry needs to play a part and broaden the scope of product reformulation beyond the reduction of nutrients to limit to increasing ingredients and nutrients in line with dietary recommendations for a healthy sustainable diet.MethodsThe Positive Nutrition Standards (PNS) were defined to increase the consumption of recommended ingredients and nutrients. The PNS were set by translating WHO and Codex guidance into product group standards, considering the role of the product group in the diet. The potential impact of the PNS for vegetables, wholegrain and fibre was modeled using data from the US NHANES 2017–2018 survey, assuming that, foods consumed would be reformulated to meet the standards where relevant.ResultsThe modeling showed that application of the PNS could increase mean population intakes by 30% for fibre, by more than 50% for vegetables and even double the intake of wholegrain. However, reformulation alone would not be sufficient to reach recommended intake levels.ConclusionThe PNS described in this paper can help to increase intakes of relevant positive nutrients and ingredients. However, a multistakeholder approach is needed to encourage consumers to make additionally required dietary shifts to meet the recommendations for positive nutrients and ingredients.

BackgroundAccording to epidemiological and experimental data, high individual dietary antioxidant intake is correlated with reduced cancer risk. The correlations between combined dietary antioxidants and the risk of all-cause and cardiovascular mortality remain unclear. Consequently, this study focused on evaluating the correlation between the food-derived Composite Dietary Antioxidant Index (CDAI) and all-cause and cardiovascular mortality.Materials and methodsTwo years of data collected from participants aged ≥20 years were included in this prospective cohort study, which was obtained from the US National Health and Nutrition Examination Survey (NHANES) from 1999 to 2018. The US NHANES adopted a complicated, multistage probability sampling method to collect health data representing the US population. Data collection was done through in-person interviews, virtual physical examinations, and laboratory tests. Mortality-related follow-up statistics from the start of the survey to 31 December 2019 were available. The shape of the correlation between CDAI and all-cause and cardiovascular mortality was inspected using a restricted cubic spline model. For CDAI and all-cause and cardiovascular mortality, the univariate- and multivariate-adjusted Cox proportional hazard models were estimated and presented as regression coefficients and 95% confidence intervals.ResultsIn total, 44,031 NHANES participants represented 339.4 million non-institutionalized residents of the US (age, 47.2 ± 16.9 years; 52.5% women, 70.2% non-Hispanic whites, 10.8% non-Hispanic black people, and 7.5% Mexican Americans). In the 118-month follow-up, 9,249 deaths were reported, including 2,406 deaths resulting from heart disease and 519 deaths due to cerebrovascular disease. In the restricted cubic spline regression models, a linear relationship between CDAI and all-cause mortality was present. The weighted multivariate hazard ratios for all-cause mortality were computed to be 0.97 (0.87–1.07) for Q2, 0.88 (0.81–0.96) for Q3, and 0.90 (0.80–1.00) for Q4 (P for trend = 0.009) upon comparison with the lowest quartile of CDAI, and an identical trend was observed for cardiovascular mortality.ConclusionA high CDAI was linked to decreased all-cause and cardiovascular mortality risk. The intake of an antioxidant-rich diet significantly prevents cardiovascular mortality. To shed more light on these outcomes, more itemized investigations such as randomized control trials are required.

An agreed-upon measure of total dietary sweetness is lacking hindering assessments of population-level patterns and trends in dietary sweetness. This cross-sectional study used 24-h dietary recall data for 74,461 participants aged ≥ 2 y from nine cycles (2001–2018) of the National Health and Nutrition Examination Survey (NHANES) to evaluate trends in the sweetness of the diet in the United States (US). LCS-containing items were matched to a sugar-sweetened counterpart (e.g., diet cola–regular cola or sucralose sugar). The matched pair was used to estimate the sugar equivalents from LCS-sweetened foods or beverages to estimate dietary level sweetness, which was described as grams of approximate sugar equivalent (ASE) per day. Trends in ASE were estimated overall and by subgroup, and trends were further disaggregated by food or beverage category. Overall, LCS sources contributed about 10.5% of ASE. Total ASE declined from 152 g/d to 117 g/d from 2001–2002 to 2017–2018 (p-trend < 0.001), with comparable declines in children and adults. Declines in total ASE were predominantly driven by beverages (−36.7% from 2001–2002 to 2017–2018) and tabletop sweeteners (−23.8%), but not food (−1.5%). Observed trends were robust to sensitivity analyses incorporating random, systematic, and sensory trial informed estimates of sweetness and also an analysis excluding possible under-reporters of dietary energy. This practical approach and underlying data may help researchers to apply the technique to other dietary studies to further these questions.