Infant formula (IF) is crucial for meeting the nutrient needs of some infants and toddlers, underscoring the need for continued monitoring of their use, composition, and contribution to nutrient intakes in this group. The objectives were to estimate among infants and toddlers aged 0 to 23 months: (1) percentage using IF, (2) mean IF nutrient content per 100 kcal, (3) percentage using IF with selected bioactives, (4) percentage using frequently reported product brands, and (5) percentage consuming both IF and dietary supplements (DSs). Data from a sample of infants and toddlers aged 0 to 23 months (n = 389) from the 2019 to March 2020 National Health and Nutrition Examination Survey were analyzed. Nearly half (45.7%) of infants and toddlers consumed IF within the past 14 days. Most IF users were infants aged 0 to 11 months: 47.7% were 0 to 5 months, 42.1% were 6 to 11 months, and about 10% were toddlers 12 to 23 months. On average, the reported IFs contained the US Food and Drug Administration–specified required nutrients in quantities within the US Food and Drug Administration standards. Some IF users (8.5%) used more than one IF product within the 2-week period. About 68% of infants and 10% of toddlers consumed an IF with docosahexaenoic acid. Additionally, 7% and 19% of infants consumed a product with probiotics or prebiotics, respectively; less than 5% used a product with both. Enfamil® RT products were used by 40.9% of IF users, Similac® RT by 38.6%, and Gerber® RT by 9.1%. Overall, 20.6% of infants and toddlers used DSs. Among IF users, 13.1% also used DSs: 16.7% aged 0 to 5 months, 10.8% aged 6 to 11 months, and 5.6% aged 12 to 23 months. Among infant IF users, the majority used products with docosahexaenoic acid, smaller percentages used products with probiotics/prebiotics, and more than one-tenth used DSs. Comprehensive dietary assessments for this age group are needed to capture accurate nutrient and bioactive intakes. Copyright © 2025 Wolters Kluwer Health, Inc All rights reserved.

BACKGROUND: Depression is a common mental health disorder. OBJECTIVE: The objective of this study was to explore the association between diet quality, as measured by the Healthy Eating Index (HEI-2020), and depression symptoms among US adolescents and young adults, 12-29 years. DESIGN: The study design was a cross sectional secondary data analysis. PARTICIPANTS: Data from the first 24-hour dietary recall for adolescents and young adults 12-29 years in the National Health and Nutrition Examination Survey 2015-March 2020 (n=4750) were analyzed. MAIN OUTCOME: Depression was defined as a score ≥10 from the Patient Health Questionnaire reflecting moderate or severe symptoms in the previous 2 weeks. STATISTICAL ANALYSES PERFORMED: HEI-2020 total (range 0-100) and component scores were calculated for those with and without depression. Predicted HEI-2020 scores were estimated from linear regression models, adjusting for age, gender, race and Hispanic origin, family income, and seeing a mental health professional in the past year. Statistical analyses accounted for the complex sample design. RESULTS: The prevalence of depression among adolescents and young adults was 7.8% (95% confidence interval (CI) 6.3-9.5%). Total HEI-2020 score was 45.9 (95% CI 45.0-46.7) out of 100 on a given day during 2015-March 2020. Among young people with depression, total HEI-2020 score was lower than among those without depression (41.7 versus 46.2, p<0.001). After adjustment for covariates, the difference was attenuated but remained significant. In adjusted analyses, HEI-2020 component scores were lower for those with depression compared to those without depression for the adequacy components: Total Fruits (1.4 vs. 1.7 p=0.03), Whole Fruits (1.2 vs. 1.7 p<0.01), Total Vegetables (2.1 vs. 2.6 p<0.01), Greens and Beans (0.8 vs. 1.2 p<0.01), and Total Protein foods (3.6 vs. 4.0 p=0.02) out of maximum scores of 5. There were no statistically significant differences observed for Whole Grains, Dairy, Seafood and Plant Proteins, Fatty Acids, Saturated Fats, Refined Grains, Sodium, or Added Sugars. CONCLUSION: Overall diet quality is low among young people. Diet quality, especially consumption of fruits, vegetables, and protein foods was lower among young people with depression compared to those without depression.

BACKGROUND: Differences in nutrient intakes by urbanization level in the U.S. is not well understood. OBJECTIVE: Describe, by urbanization level: 1) intake of protein, fiber, percent of energy from added sugars (AS) and saturated fat (SF), calcium, iron, potassium, sodium, and vitamin D; 2) the percent of the population meeting nutrient recommendations. METHODS: 24-hour dietary recalls from 23,107 participants aged 2 years and over from the 2013-2018 National Health and Nutrition Examination Surveys were analyzed. Usual intakes were estimated, and linear regression models adjusted for age, sex, race and Hispanic origin, and whether family income met the 130% threshold examined intake differences by urbanization levels-large urban areas (LUA), small to medium metro areas (SMMA), and rural areas (RA). RESULTS: A small percentage of the population met the nutrient recommendations, except for protein (92.8%) and iron (70.5%). A higher percentage of the population met recommendations than SMMA and RA for fiber (11.8% vs. 8.1% and 5.3%, p<0.001), AS (40.2% vs. 33.4% and 31.3%, p<0.001), SF (26.8% vs. 18.2% and 20.1%, p<0.001), and potassium (31.5% vs. 25.5% and 22.0%, p<0.001). Mean protein intake were also higher in LUA than RA (80.0g vs. 77.7g, p=0.003) and fiber intake higher in LUA than SMMA (16.5g vs. 15.9g, p=0.01) and RA (16.5g vs. 15.2g, p=0.001). Additionally, contributions to energy intake were lower in LUA than SMMA for AS (11.3% v 12.0%, p<0.001) and SF (11.5% v 11.7%, p<0.001), and for LUA than RA for AS (11.3% v 12.9%, p<0.001) and SF (11.5% v 11.8%, p<0.001). CONCLUSIONS: Rural areas had some markers of poorer diet quality-lower protein and fiber intake and higher AS intake-compared to large urban areas, and these differences persisted in adjusted regression models. These results may inform public health efforts to address health disparities by urbanization levels in the U.S.

BACKGROUND: Research suggests that the effects of saturated fat (SF) on health differ depending on its food source. Dairy SF has been associated with lower cardiovascular disease (CVD) risk, while meat SF is linked to a higher CVD risk. OBJECTIVES: To estimate the contribution to total intake of SF of, (1) 5 food groups - dairy, meats, seafood, plants, and "other", and (2) the top 10 specific food category sources in the US population overall and by sociodemographic subgroup. METHODS: Analysis included data from 11,798 participants in the 2017-March 2020 NHANES aged 2+ years. Grams of SF from the food sources, expressed as a percentage of the total grams of SF consumed, were estimated using the population ratio method. RESULTS: Mean daily intake of SF was 28.1g (95% CI: 27.6-28.6g), comprising 11.9% (95% CI: 11.7-12.1%) of total energy intake. Dairy contributed 28.4% of SF, followed by meats (22.1%), plant sources (7.5%), fish and seafood (1.2%), and the remaining foods (41.6%). Youth had higher SF intake from dairy than adults (p<0.001), while non-Hispanic Whites had higher intake than non-Hispanic Blacks (NHB) (p<0.001) and Hispanics (p=0.016). Adults had higher SF intake from meats than youth (p=0.002), males more than females (p<0.001), and NHB more than non-Hispanic Asians (P=0.016) and Hispanics (P<0.001). The top 10 specific sources of SF were unprocessed red meats, sweet bakery products, cured meats, milk, cheese, pizza, unprocessed poultry, Mexican mixed dishes, eggs, and combined fruits and vegetables. CONCLUSIONS: Although dairy contributed about 30% of SF compared to about 20% for total meat, the top specific food category source of SF was unprocessed red meats, which ranked in the top 2 food category sources of SF for most subgroups. These findings may be useful for further research to examine the relationship between the different sources of SF and health outcomes.

BACKGROUND: Differences in food access, availability, affordability, and dietary intake are influenced by the food environment, which includes outlets where foods are obtained. These differences between food outlets within rural and urban food environments in the US are not well understood. OBJECTIVE: The aim of this analysis was to describe the contribution of foods and beverages from six outlets - grocery stores, convenience stores, full-service restaurants, quick-service restaurants, schools, and other outlets - to total energy intake and Healthy Eating Index (HEI)-2015 scores in the US population, by urbanization level (non-metropolitan statistical areas (MSA), small to medium MSA, and large MSA). DESIGN: Data were from the National Health and Nutrition Examination Survey 2013-2018. Dietary intake from one 24-hour dietary recall was analyzed by the outlet where a food or beverage was obtained and by urbanization. Linear regression, adjusted for sex, age, race and Hispanic origin, and family income, was used to predict the contribution of each food outlet to total energy intake and HEI-2015 total and component scores by urbanization level. RESULTS: During 2013-2018, foods and beverages from grocery stores, quick-service, and full-service restaurants provided 62.1%, 15.1% and 8.5% of energy intake, respectively. The percent of energy intake from full- and quick-service restaurants increased with increasing urbanization level. HEI-2015 total scores increased with increasing urbanization level overall (48.1 non-MSAs, 49.2 small to medium MSAs, and 51.3 large MSAs), for grocery stores (46.7 non-MSAs, 48.0 small to medium MSAs, and 50.6 large MSAs), and for quick-service restaurants (35.8 non-MSAs, 36.3 small to medium MSAs, and 37.5 large MSAs). CONCLUSION: Grocery stores and restaurants were the largest contributors of energy intake in urban and rural areas. Diet quality improved with increasing urbanization overall and for grocery stores and quick-service restaurants.

BACKGROUND: The 2020-2025 Dietary Guidelines for Americans (DGAs) recommend intake of a variety of vegetables, including dark green, red and orange, starchy, and other vegetables. OBJECTIVES: This study aims to describe sociodemographic differences in the contribution of different categories of vegetables, and the form in which they are consumed, i.e., discrete vegetables, mixed dishes, and other foods such as savory snacks to total vegetables intake on a given day. DESIGN: This is a cross-sectional, secondary analysis of the 2017-2018 National Health and Nutrition Examination Survey (NHANES). PARTICIPANTS: /Setting: This study included the data of 7122 persons aged 2 years with reliable day 1 24-hour dietary recalls. MAIN OUTCOME MEASURES: Serving equivalents of vegetables from 20 discrete categories of vegetables, and from mixed dishes and other foods as a percentage of total vegetables. STATISTICAL ANALYSES: Pairwise differences by age, sex, and race and Hispanic origin, and family income were examined using univariate t statistics, and trends by age and income examined using orthogonal polynomials. RESULTS: Mean serving equivalents of vegetables was 1.4 cups. The serving equivalents increased with age among youth, was higher among non-Hispanic Asian (NHA) persons than other subgroups and increased with increasing family income. Overall, discrete vegetables contributed 55.2% of total vegetable intake and the contribution increased with age in adults, and with increasing family income. The top five discrete vegetable contributors were other vegetables and combinations, French fries and other fried white potatoes, lettuce and lettuce salads, mashed potatoes and white potato mixtures, and baked or boiled white potatoes. Non-starchy discrete vegetables contributed more to total vegetables for adults (37.6%) than youth (28.0%), and the contribution increased with increasing family income. On the other hand, the contribution of mixed dishes and other foods decreased with increasing family income. CONCLUSIONS: Discrete vegetables only contributed 55.2% of total vegetables intake, and the top sources were not varied, three of them potato-based, which may explain the reported low vegetables intake, relative to the DGAs. More than one-third of vegetables consumed were non-starchy discrete vegetables, many of which are high in vitamins. Non-starchy discrete vegetable intake was higher in adults than youth and increased with family income.