Coffee, obtained from various sources, is consumed by most United States adults. The present analyses of one and two 24-h dietary recalls for 14,865 persons aged ≥20 years in the 2011–2016 National Health and Nutrition Examination Survey (NHANES 2011–2016) aimed to identify socio-demographic predictors of coffee consumption and to examine whether coffee purchase locations differed by population sub-group. Given the emphasis on food and beverage consumption patterns, the relation between coffee consumption and compliance with the Dietary Guidelines of Americans was also examined. Coffee was consumed by 59% of the sample (n = 8551). Survey-adjusted mean intake among consumers was 544.7 g/day. Percent consumers and mean amounts consumed were highest among adults aged 51–70 years (p < 0.001), higher income groups (p < 0.001), and non-Hispanic Whites (p < 0.001). About 74% of coffee consumers obtained their coffee from stores, 9.8% from fast food restaurants, 4.3% from convenience stores, and 4.2% from someone else. Coffee source locations also varied by age, education, income, and race/ethnicity. Coffee consumers had significantly higher Healthy Eating Index (HEI-2015) and higher Nutrient-Rich Foods (NRF9.3) scores in energy-adjusted models and significantly higher HEI 2015 scores in multivariable models. In multivariable models, coffee consumers had diets with less added sugar (p < 0.001) but slightly more fat (of all types, including monounsaturated (MUFA), polyunsaturated (PUFA), saturated and solid fats), cholesterol, and alcohol. Their diets had more potassium and magnesium (p < 0.001) but less vitamin C (p < 0.001). Mean caffeine consumption was 233 mg/day for consumers and 72.3 mg/day for non-consumers. Coffee consumption patterns in the US vary across socio-demographic groups.

Flavonoid-rich tea offers an alternative to sugar-sweetened beverages. The present analyses, based on 2 24-hour dietary recalls for 17,506 persons aged ≥9 years old in the 2011–2016 National Health and Nutrition Examination Survey database (NHANES 2011–2016), explored tea consumption patterns in relation to demographics, diet quality, cardiovascular disease (CVD) biomarkers (lipids and blood pressure), and body weight. Beverage categories were unsweetened tea, other tea (herbal and presweetened tea), coffee, milk, 100% juice, water and other high-calorie (HC) and low-calorie (LC) beverages. Tea consumption (18.5% of the sample) was highest among older adults (51–70 years old), non-Hispanic Asians and Whites, and those with college education and higher incomes. The effects of age, gender, education, income, and race/ethnicity were all significant (p < 0.001 for all). Adult tea consumers had diets with more protein, fiber, potassium, iron, and magnesium, and less added sugars and alcohol. Their diets contained fewer HC beverages and coffee but had more total and citrus fruit, more total dark green and orange vegetables, and more seafood, eggs, soy and milk. Tea consumers had higher Healthy Eating Index (HEI-2015) and higher Nutrient-Rich Foods (NRF9.3) nutrient density scores. Few children drank tea and no differences in diet quality between consumers and non-consumers were observed. Adult tea consumers had slightly higher high-density lipoprotein (HDL) cholesterol and lower body mass index (BMI) values. Tea consumption was associated with higher socioeconomic status and better diets.

The quality of dietary patterns can be optimized using a mathematical technique known as linear programming (LP). LP methods have rarely been applied to individual meals. The present LP models optimized the breakfast meal for those participants in the nationally representative National Health and Nutrition Examination Survey 2011–2014 who ate breakfast (n = 11,565). The Nutrient Rich Food Index (NRF9.3) was a measure of diet quality. Breakfasts in the bottom tertile of NRF9.3 scores (T1) were LP-modeled to meet nutrient requirements without deviating too much from current eating habits. Separate LP models were run for children and for adults. The LP-modeled breakfasts resembled the existing ones in the top tertile of NRF9.3 scores (T3), but were more nutrient-rich. Favoring fruit, cereals, and dairy, the LP-modeled breakfasts had less meat, added sugars and fats, but more whole fruit and 100% juices, more whole grains, and more milk and yogurt. LP modeling methods can build on existing dietary patterns to construct food-based dietary guidelines and identify individual meals and/or snacks that need improvement.

Dietary Guidelines for Americans 2015–20 recommend replacing sugar sweetened beverages (SSBs) with plain water in order to promote adequate hydration while reducing added sugar intake. This study explored how water intakes from water, beverages, and foods are distributed across the day. The dietary intake data for 7453 children (4–18 y) and 15,263 adults (>19 y) came from the National Health and Nutrition Examination Survey (NHANES 2011–2016). Water was categorized as tap or bottled. Beverages were assigned to 15 categories. Water intakes (in mL/d) from water, beverages, and food moisture showed significant differences by age group, meal occasion, and time of day. Plain water was consumed in the morning, mostly in the course of a morning snack and between 06:00 and 12:00. Milk and juices were consumed at breakfast whereas SSBs were mostly consumed at lunch, dinner, and in the afternoon. Children consumed milk and juices, mostly in the morning. Adults consumed coffee and tea in the morning, SSBs in the afternoon, and alcohol in the evening. Relatively little drinking water was consumed with lunch or after 21:00. Dietary strategies to replace caloric beverages with plain water need to build on existing drinking habits by age group and meal type.

The contribution of breakfast to diet quality (DQ) can inform future dietary guidelines. This study examined breakfasts that were associated with highest-quality diets. Dietary data came from the first reported day of the National Health and Examination Survey (NHANES) 2011-2014 (n=14,488). DQ measures were the Nutrient Rich Foods Index (NRF9.3) and the USDA Healthy Eating Index 2015 (HEI 2015). Analyses of breakfast intakes were conducted by NRF9.3 tertiles and by age and socioeconomic groups. Four out of 5 NHANES participants ate breakfast. Breakfast provided 19-22% of dietary energy depending on age. Breakfast intakes of complex carbohydrates and total sugars were higher and intakes of protein and fats were lower relative to energy intakes. Breakfast provided more that 20% of daily intakes of B vitamins, vitamins A and D, folate, calcium, iron, potassium and magnesium. Eating breakfast was associated with higher NRF9.3d scores. Breakfasts associated with top tertile of NRF9.3d had more carbohydrates and less added sugars and fats. Such breakfasts had more fruit and juices, more whole grains, more milk and yogurt and less meat and eggs. Breakfast patterns that favored fruit, whole grains, and dairy were associated with healthiest diets.