Abstract
Background:
Adolescents need nutrient-dense foods for growth, and eggs are a nutritious option to help meet nutrient needs.
Objectives:
This study aimed to assess the relationship between egg-consumption categories and nutrient intake, nutrient adequacy and nutrient exposure scores among US adolescents.
Methods:
Adolescents in the 2007–2018 NHANES (14–17 y; n = 3691) with at least one 24-h dietary recall and supplement data were included. Egg consumption was categorized as nonegg consumer, consumer of eggs as ingredients, or consumer of a primarily egg dish. Usual nutrient intakes, nutrient adequacy, and nutrient exposure scores for intakes from all sources [i.e., total nutrient index (TNI); scored 0–100; foods + supplements] and foods alone [i.e., Food Nutrient Index (FNI); 0–100] were estimated using the National Cancer Institute method. Pairwise t-tests compared the nutrient markers across the 3 egg-consumption groups.
Results:
US adolescents failed to meet various nutrient adequacy markers, highlighting a high risk of inadequacy for calcium, magnesium, vitamin D, and vitamin E, and a low percentage above the adequate intake for choline. Primarily egg dish consumers exhibited higher mean usual intakes for lutein + zeaxanthin, choline, vitamin A, selenium, vitamin D, riboflavin, docosahexaenoic acid (DHA), and protein than nonegg consumers; and for lutein + zeaxanthin, choline, selenium, and DHA than those consuming eggs as ingredients (P < 0.001). Consuming eggs as ingredients showed higher iron and vitamin E intakes compared with not consuming eggs. Consumers of eggs, either primarily dishes or as ingredients had higher TNI scores (P < 0.001) for total (76 and 71 compared with 65), magnesium (69 and 66 compared with 60) and potassium (83 and 80 compared with 73) and FNI scores for potassium (82 and 80 compared with 73) than nonegg consumers, respectively.
Conclusions:
US adolescents consuming eggs, as primarily dishes or ingredients, had better compliance in meeting nutrient markers compared with nonegg consumers, highlighting associations between eggconsumption and nutrient intake.
Keywords: nutrient intake, eggs, adolescents, NHANES, dietary intake
Introduction
The second most rapid phase of linear growth in life, exceeded only by infancy, is adolescence. During this time, proper nutrition to fulfill energy needs and essential nutrient requirements to support bodily functions and growth [1] is crucial for optimal health outcomes in adulthood that set the foundation for long-term well-being [2]. Despite the importance of nutrition during this time, adolescence is characterized by low diet quality and high inadequacy for multiple nutrients and food components, more so than in any other life stage [2] especially among adolescents aged 14–18 y [3,4].
The 2025 Scientific Report of the Dietary Guidelines for Americans (DGA) Advisory Committee described that adolescents commonly fall short of the estimated average requirement (EAR) for micronutrients such as vitamins A, B-6, B-12, C, E, folate, and phosphorus, as well as the adequate intake (AI) for choline and potassium [4]. Adolescents aged 14–18 y are at a greater risk of inadequate nutrient intake compared with other age groups, which is especially concerning given that this life stage involves rapid growth, hormonal changes, the onset of puberty, and, for females, the initiation of menstruation [3,4]. Adolescent females have increased iron requirements and are more likely to have inadequate intakes of iron, which increases the risk of iron deficiency [4]. Additionally, ~8% of males and 23% of females in this age group consume less protein than the EAR [4]. Deficiencies in nutrients essential for bone development, including vitamin D, calcium, magnesium, and zinc, are also widespread among adolescents [4]. This unique constellation of nutrient inadequacies during adolescence may be influenced, in part, by the evolving eating behaviors that typically emerge during this developmental stage [3].
Adolescent eating behaviors may shift considerably as they begin to exercise more autonomy in their food choices, often seeking out meals that align with their personal taste preferences and lifestyles [3,5]. This developmental shift in eating behaviors distinguishes older from younger adolescents (e.g., 12 and 13 y olds), who are generally more influenced by parental or caregiver control over food selection and consumption [3]. A qualitative study among US adolescents (13–17 y) found that convenience and ease of preparation are the predominant factors influencing their food choices at home, school, restaurants, and stores [5]. These 2 factors may, in part, provide rationale as to why eggs are a popular food choice among this age group [6]. Indeed, on any given day, ~12% of children and adolescents (2–19 y) consume eggs as an individual item or in an omelet, and 5% as an egg sandwich [7]. Eggs are commonly featured in both quick, simple dishes like scrambled eggs and omelets and in more complex recipes such as souffles [8]. They may also be consumed in meals throughout the day making them a protein-rich food source for adolescents with varying levels of culinary skills. The high protein composition of eggs provides essential amino acids necessary for growth and tissue repair [9,10] and accounts for their inclusion in the protein food group as one of the 5 main food groups of the USDA Food Patterns [11] that are recommended for meeting protein and nutrient requirements of the 2020–2025 DGA [3]. Additionally, the National School Breakfast Program (NSBP), which is aligned with the dietary patterns of the DGA, incorporates eggs into cycle menus based on balanced breakfast options (e.g., omelet quesadilla, egg tacos) [12,13]. Incorporation of eggs and protein-rich food sources into these menus, in combination with other nutrient-dense food groups, supports healthy dietary habits among school-aged adolescents [3,14,15]. Eggs contain a variety of vitamins, minerals and macronutrients, including lutein, zeaxanthin, choline, B vitamins, vitamins D and E, as well as calcium, folate, iron, magnesium, potassium, selenium, zinc, DHA, protein and others [10], several of which are nutrients commonly underconsumed by adolescents [3,4]. Compared with red meat and dairy products, eggs also provide these nutrients with less saturated fat; however, they also contain dietary cholesterol, which has been linked, though inconsistently, to an increased risk of cardiovascular disease [4].
Consumption of primarily egg foods like boiled eggs and even foods that include eggs as ingredients (e.g., quiche) may help meet nutrient recommendations among US adolescents. Food-insecure adolescents have limited access to enough food for an active, healthy life and are particularly at risk for poor dietary outcomes [16]. A prior analysis evaluated the association between usual nutrient intake and egg-rich diets stratified by food security [17] and determined egg-rich diets show improved nutrient adequacy for those who were food insecure. Therefore, stratifying by egg-rich diets alone in this study will allow isolation of the specific contribution of egg consumption to nutrient intake in adolescents, independent of other factors like food security status. Understanding the dietary behavior of egg consumption among US adolescents can help to identify potential areas for dietary interventions and to inform public health strategies aimed at improving adolescent nutrition.
This analysis aimed to assess the relationship between the egg-consumption categories (i.e., not consuming eggs, consuming eggs as ingredients in dishes, and consuming primarily egg dishes) and nutrient intake, nutrient adequacy, and scores of total and dietary-source nutrient exposure utilizing the total nutrient index (TNI) and Food Nutrient Index (FNI) among US adolescents (14–17 y) of the 2007–2018 NHANES.
Methods
Study participants
The NHANES includes the resident, civilian, noninstitutionalized US population in an ongoing, nationally representative, cross-sectional survey for diet and health surveillance and monitoring [18]. An interview in the participant’s home, a health examination at a mobile examination center (MEC), and a telephone interview are part of the NHANES data collection. All participants and/or their proxies provide written informed consent, and the NHANES study protocol is approved by the National Center for Health Statistics Institutional Review Board [19]. For this analysis, 2 analytic samples were included. The first sample included adolescents aged 14–17 y with ≥1 complete and reliable 24-h dietary recall from 6 combined survey cycles, before the emergence of the COVID19 pandemic, a period associated with changes in dietary behaviors, 2007–2018 (n = 3691) (Supplementary Figure 1) to create a sample large enough to support reliable and stable estimates. This sample was used to calculate the mean usual nutrient intakes and nutrient adequacy [18]. The second sample consisted of 1822 adolescents aged 14–17 y, which is a subsample of the 3691 with complete data regarding use of dietary supplements (DS) [i.e., Dietary Supplement and Prescription Medicine Questionnaire (DSMQ)] and with at least one 24-h dietary recall. The second sample was utilized to estimate the TNI and FNI scores (Supplementary Figure 1).
Demographic and socioeconomic information
Participants ≥16 y and a proxy for those aged ≤15 y reported demographic and socioeconomic data through an in-home interview. Participants self-reported their race and Hispanic origin, which were categorized as Mexican American, other Hispanic, non-Hispanic White, non-Hispanic Black, and other race/ethnic groups. The comparison of the family’s annual income to the poverty guideline set by the Department of Health and Human Services was estimated via the family poverty-to-income ratio (PIR) and classified in 4 categories as: <1.00–<1.30, <1.30–<1.85, 1.85 and ≥1.85. These PIR thresholds align with eligibility criteria commonly used to determine qualification for federal child food assistance programs, providing meaningful context for interpreting socioeconomic status in relation to diet and nutrition outcomes [20]. Participants reported information on their household’s participation in the Supplemental Nutrition Assistance Program (SNAP), which provides a benefit to low-income households to enable them to purchase foods [21]. The household’s participation in the SNAP came from the question “In the last 12 months, did you or any member of your household receive SNAP or Food Stamp benefits?” which is included in the food security datafile of the questionnaire data. Adolescents receiving benefits from the National School Lunch Program (NSLP) and the NSBP were also identified using the questions “During the school year, about how many times a week {do you/does sample person (SP)} usually get a complete school lunch? and a complete breakfast at school?” from the Diet Behavior and Nutrition datafile of the questionnaire data. Centers for Disease Control and Prevention growth charts defined obesity as having a BMI (kg/m2) at or above the 95th percentile specific to age and gender. The physical health examination conducted in the MEC provided data on height (in m) and weight (in kg). These measurements were used in this analysis to estimate the BMI using the growth charts of the Centers for Disease Control and Prevention [22].
Dietary intake and supplement intake assessment
Dietary intake from foods and beverages was assessed through a maximum of two 24-h dietary recalls [23]. A face-to-face interview was carried out at the MEC for the first dietary recall, whereas the second was via telephone ~3–10 d later [18]. All participants in this analysis (aged 14–17 y) self-reported comprehensive descriptions of all foods and beverages from midnight to midnight on the preceding day to a trained NHANES interviewer during both recalls, using the validated USDA Automated Multiple Pass Method [23,24]. Several versions of the USDA’s Food and Nutrient Database for Dietary Studies (FNDDS) were utilized to estimate the nutrient content from all reported foods and beverages [2007–2008 (version 4.1), 2009–2010 (version 5.0), 2011–2012, 2013–2014, 2015–2016, and 2017–2018] [25]. DS use and intake from DS were derived from the DSMQ completed in the in-home interview. DS usage was determined based on participants’ affirmative responses to questions about consuming any DS products, over the past 30 d. Participants were asked to present containers for each dietary supplement they reported and to provide information on the frequency of use, dosage, and length of time they had taken the supplement. Children ≥16 y self-reported their DS usage whereas a proxy reported for those younger. The NHANES Dietary Supplement Database was utilized to estimate the nutrient values for DS [26,27].
Categories of egg-consuming behavior
Egg-consuming behavior was identified using the dietary data from day 1, 24-h recall to facilitate equal probability for classification to egg-consuming groups among the sample and also to represent data collected by an onsite interviewer. Each individual was categorized into 1 of 3 mutually exclusive categories based on the presence and type of egg-containing foods, rather than the quantity consumed: nonegg consumer, consumer of eggs as ingredients in dishes, or primarily egg dish consumer. Consumers of primarily egg dishes were identified based on reported consumption of foods classified under the What We Eat in America (WWEIA) food category “Eggs and omelets” and “Egg sandwiches” which corresponds to FNDDS food categories 2502 and 3706, respectively [28]. These categories include FNDDS food codes typically representing primarily egg-based dishes, such as scrambled eggs or omelets [28]. The WWEIA categories are designed to reflect how Americans commonly consume foods and are built on the more detailed FNDDS food codes, allowing for a practical grouping of similar items [28]. Although these categories include foods that often contain additional ingredients (e.g., scrambled eggs with milk or cheese), these items were considered primarily egg-based given that eggs are the central and defining ingredient in their preparation. Certain foods in this category were excluded from this classification including “egg substitute, unspecified whether powdered, frozen, or liquid” and nonchicken eggs like “duck,” “goose,” and “quail.” Individuals typically consume mixed dishes rather than single, isolated foods. As a result, some foods within this category may have been consumed as part of composite meals, such as garden salad with a boiled egg, where eggs were not necessarily the primary component.
The consumers of eggs as ingredients in dishes included participants who reported foods that contained eggs as a secondary or minor ingredient (e.g., breads, breakfast tarts, cakes), but who did not consume any food from the primarily egg dish category. Foods labeled as “low fat,” “cholesterol free,” “reduced fat,” or “fat free” were excluded because it could not be verified using the label (e.g., description of foods) whether eggs were part of those dishes. Adolescents who consumed both a primarily egg dish and a food with eggs as an ingredient were classified under the primarily egg dishes category. Those who consumed multiple dishes with eggs as ingredients were categorized in the eggs as ingredients group. Adolescents who did not report consuming any primary egg dishes or dishes containing eggs as an ingredient were classified as nonegg consumers.
Usual nutrient intake and the proportion of adolescents meeting indicators of nutrient adequacy
Usual intakes for nutrients that are of public health concern [3] and those for which there is a higher risk of inadequacy [29–31] were approximated using the National Cancer Institute (NCI) method [32]. This statistical modeling technique estimates group-level means and distributions of usual intake from individual self-reported 24-h recalls, adjusting for random measurement error (i.e., day-to-day variation) [30]. Nutrients included in this analysis were calcium, choline, DHA, folate, iron, lutein + zeaxanthin, magnesium, potassium, protein, selenium, and vitamins A, thiamin, riboflavin, niacin, vitamin B-6, B-12, C, D, and E, and zinc [33–39] from foods and beverages alone; without including nutrients from DS. These nutrients were selected due to low intakes among adolescents, and their inclusion within the composition of eggs [4,10]. The proportion of adolescents below the EAR or above the AI, respectively, at the group level was also estimated using the NCI method; the EAR was selected as a cut-point as it represents the median usual nutrient intake for which 50% of the healthy population’s needs are met. The proportion of the population below this indicator reflects the proportion of the population at increased risk of inadequate nutrient intakes (the EAR cut-point method) [40]. The cut-point was used for all nutrients, including iron [40]. Some nutrients do not have sufficient scientific evidence to establish an EAR, and in these cases, the AI is used. The AI represents the mean daily nutrient intake considered adequate for a healthy population’s needs and for these nutrients the proportion above the AI is determined [40]. SEs were estimated using Fay’s modified balanced repeated replication method with a Fay coefficient of 0.3 [41,42].
Recommendations for the grams of protein, as a nutrient, within the DGA were based on the kilocalorie level per day for sex/life stage groups and the Acceptable Macronutrient Distribution Range. The DGA offers science-based guidelines on food and beverage choices to promote health, reduce the risk of chronic diseases, and meet nutrient needs [3]. For this study, lower kilocalorie levels were used to estimate protein needs because teens tend to be sedentary [39] and girls eat less protein than boys [3]. According to the DGA, adolescent girls and boys need about 1800–2400 kcal/d and 2000–3200 kcal/d, respectively [3]. The DGA recommends that 10%–30% of total calories come from protein, with a minimum of 46 g for adolescent girls in 1800 kcal/d, and 52 g for boys in a 2200-kcal/d, so these protein amounts (46 and 52 g) were used as cut-points to determine the percentage of adolescents meeting the DGA protein recommendation [3].
Estimating the total nutrient intake and food nutrient intake
The TNI is a scoring system based on micronutrients that evaluates total nutrient intake from foods, beverages, and DS relative to the dietary reference intakes for underconsumed micronutrients identified as of public health relevance by the DGA. The FNI accounts for nutrients from foods and beverages only, and it is calculated in the same way as the TNI but excludes nutrient contributions from DS, making it identical to the TNI for individuals who do not use DS [43,44]. The TNI and FNI scores have previously distinguished groups with known differences in dietary quality and correlated well with biomarkers of nutritional status, exhibiting relative validity [43,44]. In the present analysis, the NCI simple algorithm method was used to derive TNI and FNI scores. Eight micronutrients were prioritized for inclusion as the component scores in the calculation of the TNI and FNI: calcium, magnesium, potassium, zinc, choline, folate, and vitamins C and D, due to their high rates of under-consumption among US adolescents. Usual nutrient intakes for each micronutrient were expressed as a percentage of the age- and sex-specific recommended dietary allowances (RDA) and AI, ranging from 0 to 100. For the TNI and FNI component scores, higher scores indicate a closer alignment with the RDA or AI. Then, the total TNI and FNI scores were calculated as the average of the 8 component scores, with each component receiving equal weight [43,44].
Statistical analysis
The first analytical sample (n = 3691) was separated into distinct egg-consumption groups as: nonegg consumer (n = 1797, 47%), consumer of eggs as ingredients in dishes (n = 1329, 39%), or primarily egg dish consumer (n = 565, 14%). Rao–Scott F adjusted χ2 tests, with a 2-sided P value of < 0.05, were performed across the egg-consumption groups to determine if there were significant differences in characteristics based on egg consumption. The second analytical sample (n = 1822) was also divided into the same 3 egg-consumption groups (e.g., nonegg consumers, consumer of eggs as ingredients in dishes or primarily egg dish consumers) to examine differences in total and component scores for the TNI and FNI. For all usual nutrient intake distribution estimates, adjustments were made for covariates day of the recall (weekday compared with weekend) and the sequence of the recall (first compared with second). Sociodemographic characteristic variables that were significantly distributed among the groups were found to be correlated with one another (e.g., PIR or SNAP participation) thus, to prevent multicollinearity, adjustments for these characteristics were not applied to the usual intake estimates. Significant differences in mean usual nutrient intake, proportion of adolescents below the EAR or above AI, and mean TNI and FNI scores across the 3 egg-consumption groups, were determined using pairwise t tests. A Bonferroni-adjusted P value was calculated based on the number of comparison groups for all nutrients or nutrient scores and varied depending on the group included in that analysis to adjust for multiple comparisons. Statistical analyses were conducted using SAS 9.4 (SAS Institute). Survey weights were applied to produce nationally representative estimates, and variance estimation, data subsetting, and the complex sampling design of NHANES were accounted for in all analyses [45].
Results
Egg consumption among adolescents can be categorized as follows: 14% consumed primarily egg dishes, 39% consumed eggs as ingredients in dishes, and 47% did not consume eggs (Table 1). Overall, 55%–62% of adolescents were non-Hispanic White, 54%–61% had a PIR >1.85, 17%–24% reported household SNAP participation, 48% received the NSLP 5 times per week, ~50% did not participate in the NSBP, 70%–76% were not dietary supplement users, and 54%–64% were classified as having a healthy weight.
TABLE 1.
Sociodemographic characteristics among US adolescents (14–17 y) by egg-consumption behavior, NHANES 2007–20181
| Nonegg consumers | Eggs as ingredients in dishes | Primarily egg dishes | P value2 | ||||
|---|---|---|---|---|---|---|---|
| Characteristic | n | % ±SE | n | % ±SE | n | % ±SE | |
| Total | 1797 | 47.2 ±1.1 | 1329 | 38.5 ±1.2 | 565 | 14.3 ±0.8 | |
| Sex | 0.69 | ||||||
| Boys | 923 | 50.0 ±1.5 | 675 | 49.0 ±1.7 | 299 | 52.0 ±2.8 | |
| Girls | 874 | 50.0 ±1.5 | 654 | 51.0 ±1.7 | 266 | 48.0 ±2.8 | |
| Race/ethnicity | <0.0001 | ||||||
| Mexican American | 419 | 15.0 ±1.4 | 266 | 11.0 ±1.3 | 136 | 16.0 ±1.9 | |
| Other Hispanic | 178 | 6.0 ±0.7 | 129 | 5.5 ±0.8 | 72 | 8.0 ±1.1 | |
| Non-Hispanic White | 500 | 55.0 ±2.0 | 441 | 62.0 ±2.3 | 131 | 50.0 ±3.3 | |
| Non-Hispanic Black | 461 | 15.0 ±1.1 | 310 | 13.0 ±1.2 | 147 | 16.0 ±1.8 | |
| Other race (including multiracial) | 239 | 9.0 ±0.8 | 183 | 8.5 ±0.8 | 79 | 10.0 ±1.8 | |
| Poverty income ratio | 0.03 | ||||||
| <1.00–<1.30 | 646 | 26.0 ±1.5 | 407 | 21.0 ±1.3 | 209 | 28.0 ±2.4 | |
| 1.30–<1.85 | 197 | 8.0 ±0.7 | 141 | 8.0 ±0.8 | 54 | 8.0 ±1.2 | |
| 1.85 | 230 | 11.0 ±0.9 | 168 | 10.0 ±1.0 | 67 | 10.0 ±1.6 | |
| ≥1.85 | 724 | 55.0 ±1.8 | 613 | 61.0 ±1.8 | 235 | 54.0 ±2.9 | |
| Household SNAP participating | 0.003 | ||||||
| Yes | 581 | 24.0 ±1.5 | 333 | 17.2 ±1.4 | 146 | 20.6 ±2.3 | |
| No | 207 | 11.0 ±0.9 | 163 | 11.9 ±1.0 | 81 | 13.3 ±2.1 | |
| NSLP (number of times/wk) | 0.64 | ||||||
| 0 | 342 | 22.5 ±1.4 | 290 | 25.9 ±1.5 | 118 | 25.6 ±2.9 | |
| 1–4 | 339 | 19.8 ±1.1 | 237 | 17.7 ±1.3 | 112 | 17.9 ±2.1 | |
| 5 | 963 | 48.6 ± 1.8 | 701 | 48.1 ±2.0 | 285 | 47.5 ±2.9 | |
| NSBP (number of times/wk) | 0.51 | ||||||
| 0 | 830 | 49.8 ±1.5 | 621 | 50.9 ±1.9 | 248 | 48.6 ±3.4 | |
| 1–4 | 254 | 12.2 ±0.9 | 205 | 13.3 ±1.0 | 82 | 12.8 ±1.9 | |
| 5 | 365 | 16.2 ±1.0 | 254 | 14.2 ±1.2 | 133 | 19.0 ±2.2 | |
| Dietary supplements users | 0.12 | ||||||
| Yes | 371 | 24.0 ± 1.5 | 322 | 26.0 ±1.7 | 138 | 30.0 ±2.7 | |
| No | 1426 | 76.0 ±1.5 | 1005 | 74.0 ±1.7 | 427 | 70.0 ±2.7 | |
| BMI3 (kg/m2) | 0.002 | ||||||
| Underweight | 56 | 3.0 ±0.5 | 52 | 4.0 ±0.9 | 23 | 5.0 ±1.4 | |
| Healthy weight | 1008 | 57.0 ±1.3 | 822 | 64.0 ±1.6 | 298 | 54.0 ±2.7 | |
| Overweight | 303 | 18.0 ±1.1 | 223 | 16.0 ±1.0 | 114 | 20.0 ±2.3 | |
| Obesity | 430 | 22.0 ±1.2 | 232 | 16.0 ±1.3 | 130 | 21.0 ±2.1 | |
Abbreviations: NSBP, National School Breakfast Program; NSLP, National School Lunch Program; SNAP, Supplemental Nutrition Assistance Program.
According to the directions of the Centers for Disease Control and Prevention, the complex survey design is adjusted. For some variables, percentages may not add ≤100% due to rounding or missing data.
Rao–Scott F adjusted χ2 tests were used to compare characteristics by egg-consumption behavior with a 2-sided P value of < 0.05.
BMI, underweight (<the 5th percentile), healthy weight (5th percentile to <the 85th percentile), overweight (85th percentile to < the 95th percentile), obesity (equal to or greater than the 95th percentile).
Overall, the mean usual intakes of US adolescents did not meet the requirements for several nutrients including calcium, magnesium, vitamin D, and vitamin E (except for adolescents consuming primarily egg dishes, who narrowly met the EAR for magnesium). Also, mean choline intake for most adolescents was not above the AI (Table 2). Among the 20 nutrients analyzed, significant differences in mean usual intake were observed for 10 nutrients (lutein + zeaxanthin, choline, vitamin A, selenium, vitamin D, iron, vitamin E, riboflavin, DHA, and protein) when comparing the adolescent groups based on their egg-consumption behavior. The group consuming primarily egg dishes (e.g., scrambled eggs) showed significantly higher mean usual intake (P < 0.001) for 8 of 10 previous nutrients (lutein + zeaxanthin, choline, vitamin A, selenium, vitamin D, riboflavin, DHA, and protein) when compared with nonegg consumers. Also, adolescents consuming primarily egg dishes showed significantly higher mean usual intakes (P < 0.001) for 4 of the 10 nutrients (lutein + zeaxanthin, choline, selenium, and DHA) than adolescents consuming eggs as ingredients in dishes (e.g., souffle). Furthermore, even when comparing adolescents consuming eggs as ingredients in dishes and adolescents who did not consume eggs, those consuming eggs as ingredients had significantly higher mean usual intakes for 2 of 10 nutrients (iron and vitamin E). Significant differences in mean usual intakes were noted across egg-consumption categories for some nutrients. For example, adolescents who consumed primarily egg dishes had significantly higher mean usual intake for choline (403 mg) when compared with adolescents consuming eggs as ingredients in dishes (295 mg) and who were nonegg consumers (263 mg). Similarly, mean usual intakes for lutein + zeaxanthin were significantly higher for adolescents with primarily egg dishes consumption behavior (1494 μg) followed by those consuming eggs as ingredients in dishes (1096 μg) and those with nonegg consumption behavior (1087 μg).
TABLE 2.
Comparison of mean usual nutrient intake from foods and beverages alone among US adolescents (14–17 y), by egg-consumption behavior, NHANES 2007–2018
| Nutrient | DRI1 | Nonegg consumers | Eggs as ingredients in dishes | Primarily egg dishes |
|---|---|---|---|---|
| Mean±SE (n = 1797) | Mean ±SE (n = 1329) | Mean ±SE (n = 565) | ||
| Lutein + zeaxanthin (μg) | — | 1086.6 ±68.3a | 1095.9 ± 51.6b | 1494.0 ±82.3ab |
| Choline2 (mg) | 400–550 | 262.5 ± 10.4a | 295.1 ± 7.4b | 402.6 ± 14.8ab |
| Vitamin A3 (μg) | 485–630 | 578.6 ± 22.0a | 616.9 ± 30.1 | 742.5 ± 27.2a |
| Potassium2 (mg) | 2300–3000 | 2397.8 ± 64.6 | 2621.4 ± 77.0 | 2727.1 ±75.4 |
| Folate4 (μg) | 330 | 491.2 ± 14.5 | 548.4 ±12.7 | 535.6 ±21.5 |
| Calcium (mg) | 1100 | 914.5 ± 24.6 | 1015.7 ± 25.0 | 1042.9 ±32.8 |
| Selenium (μg) | 45 | 97.9 ±3.8a | 111.3 ± 3.0b | 127.8 ±3.5ab |
| Magnesium (mg) | 300–340 | 263.6±7.5 | 299.0 ± 7.8 | 303.8 ±7.8 |
| Vitamin D (μg) | 10 | 4.5 ±0.2a | 4.9 ± 0.2 | 5.9 ±0.2a |
| Iron (mg) | 7.7–7.9 | 13.5 ±0.4a | 15.9 ± 0.2a | 15.6 ±0.4 |
| Zinc (mg) | 7.3–8.5 | 10.4 ±0.4 | 11.7 ± 0.3 | 11.8±0.3 |
| Vitamin E5 (mg) | 12 | 7.0 ±0.2a | 8.6 ±0.2a | 8.5 ±0.4 |
| Vitamin B12 (μg) | 2 | 4.7 ±0.1 | 5.3 ± 0.1 | 5.5 ±0.1 |
| Riboflavin (mg) | 0.9–1.1 | 1.9 ± 0.1a | 2.1 ± 0.0 | 2.3 ±0.0a |
| Thiamin (mg) | 0.9–1 | 1.5 ±0.0 | 1.7 ± 0.0 | 1.7 ±0.0 |
| Vitamin B6 (mg) | 1–1.1 | 1.2 ±0.0 | 2.1 ± 0.0 | 2.2 ±0.0 |
| DHA (mg) | — | 70.0 ±0.0a | 40.0± 0.0b | 70.0±0.0ab |
| Vitamin C (mg) | 56–63 | 78.9 ±6.9 | 80.1 ± 3.3 | 91.1 ±5.7 |
| Niacin (mg) | 11–12 | 23.8 ±0.5 | 26.5 ± 0.9 | 25.9 ±0.6 |
| Protein DGA (g) | 46–52 | 71.0 ±2.7a | 81.6 ± 2.6 | 88.2 ± 2.0a |
A t-test was used with a P < 0.001 to account for multiple comparisons and the Bonferroni-adjusted P value was applied. The analysis involved the 3 egg-consumption groups, leading to 3 possible pairwise comparisons (3!/(3–2)!2=3). With 21 nutrient markers, this resulted in a total of 63 (3 by 21) comparisons, which were used in the Bonferroni adjustment, dividing 0.05 by 63 to obtain a P value of 0.001. The shared letter indicates significant differences between columns.
Abbreviations: AI, adequate intake; DFE, dietary folate equivalents; DGA, Dietary Guidelines for Americans; DRI, dietary reference intakes; EAR, estimated average requirement; RAE, retinol activity equivalents.
DRI column shows the: EAR or AI, and the protein recommendation according to the DGA. EAR or AI ranges for adolescents aged 14–18 y are dependent on sex, — no official DRI (data not shown).
Estimated using the AI as an EAR is not established.
Estimations of vitamin A as RAE.
Estimations of folate, as DFE.
Estimations of vitamin E, as alpha tocopherol.
All adolescents showed a high prevalence of inadequacy for several nutrients (Table 3). However, adolescents consuming primary egg dishes had a lower risk of inadequacy (~10%) for vitamin A, potassium, calcium, magnesium, zinc, and protein when compared with those who did not consume eggs at all. Additionally, a greater proportion of adolescents in the primarily egg dish group had choline intakes above the AI compared with nonegg consumers.
TABLE 3.
Estimated prevalence of usual nutrient intakes, from foods and beverages alone, less than the estimated average requirement, Dietary Guidelines for Americans protein recommendations or above the AI among US adolescents (14–17 y), by egg-consumption behavior, NHANES 2007–2018
| Nutrient | Daily reference intake1 | Nonegg consumers | Eggs as ingredients in dishes | Primarily egg dishes |
|---|---|---|---|---|
| % ±SE (n = 1797) | % ±SE (n = 1329) | % ±SE (n = 565) | ||
| Choline2 (mg) | 475 | 7.1 ±1.2 | 11.3 ±1.2 | 30.8 ±2.9 |
| Vitamin A3 (μg) | 485–630 | 56.3 ± 2.4 | 52.4 ±3.4 | 40.0 ±2.4 |
| Potassium2 (mg) | 2300–3000 | 21.5 ±6.5 | 44.1 ±2.9 | 48.1 ±2.6 |
| Folate4 (μg) | 330 | 28.1 ±2.0 | 20.9 ±1.5 | 22.3 ±2.6 |
| Calcium (mg) | 1100 | 72.0 ±2.1 | 63.6 ±2.1 | 61.3 ±2.8 |
| Selenium (μg) | 45 | 6.8 ±1.2 | 3.6 ±0.6 | 1.6 ±0.3 |
| Magnesium (mg) | 300–340 | 73.4 ±2.3 | 62.3 ±2.4 | 60.7 ±2.4 |
| Vitamin D (μg) | 10 | 91.7 ±0.9 | 90.0 ±1.0 | 84.8 ±1.4 |
| Iron (mg) | 7.7–7.9 | 16.3 ±1.9 | 8.5 ±0.7 | 9.3 ±1.2 |
| Zinc (mg) | 7.3–8.5 | 33.3 ±3.1 | 24.4 ± 2.2 | 23.6 ±1.9 |
| Vitamin E5 (mg) | 12 | 89.7 ±1.4 | 80.3 ±1.6 | 80.9 ±2.7 |
| Vitamin B-12 (μg) | 2 | 15.7 ±1.5 | 12.1 ±1.2 | 10.7 ±1.1 |
| Riboflavin (mg) | 0.9–1.1 | 13.3 ±1.5 | 8.1 ±0.7 | 5.3 ±0.7 |
| Thiamin (mg) | 0.9–1 | 19.1 ±1.8 | 11.6 ±1.0 | 11.7 ±1.7 |
| Vitamin B-6 (mg) | 1–1.1 | 17.4 ±1.5 | 12.2 ±1.7 | 11.0 ±1.4 |
| Vitamin C (mg) | 56–63 | 47.9 ±4.8 | 47.2 ± 2.3 | 40.3 ±3.3 |
| Niacin (mg) | 11–12 | 9.4 ±0.9 | 5.9 ±1.0 | 6.6 ±0.8 |
| Protein DGA (g) | 46–52 | 23.7 ±2.9 | 14.6 ±1.9 | 10.4 ±0.5 |
Abbreviations: AI, adequate intake; DFE, dietary folate equivalents; DGA, Dietary Guidelines for Americans; EAR, estimated average requirement; RAE, retinol activity equivalents
Dietary reference intake column shows the: EAR or AI, and the protein recommendation according to the DGA. EAR, AI, and DGA ranges for adolescents aged 14–18 y are dependent on sex.
Estimated using the AI as an EAR is not established.
Estimations of vitamin A as RAE.
Estimations of folate, as DFE.
Estimations of vitamin E, as alpha tocopherol.
Adolescents consuming primary egg dishes showed ≥5% lower prevalence of inadequacy for vitamin A, vitamin D, and vitamin C when compared with those who consumed eggs only as ingredients in dishes. In general, adolescents consuming primarily eggs dishes showed less nutrient inadequacies than the 2 other groups. For example, between 90% and 92% of adolescents who were nonegg consumers did not meet the EARs for vitamin D and vitamin E whereas ~81%–85% of adolescents consuming primarily egg dishes did. For nutrients with an AI, such as choline, the prevalence of intake above the AI was compared. In this case, only 7% of nonegg consumers and 11% of adolescents consuming eggs as ingredients in dishes were above the AI for choline, whereas 31% of those consuming primarily egg dishes were above the AI. Among adolescents who consumed either primarily egg dishes or eggs as ingredients, ~60%–64% of adolescents did not achieve the EAR for calcium and magnesium, whereas >70% did not achieve the EAR among nonegg consumers. Similarly, between 48% and 56% of adolescents who were nonegg consumers and who were consuming eggs as an ingredient in dishes did not achieve vitamin A and vitamin C average requirements, whereas ~40% did not achieve these requirements among those who consumed primarily egg dishes. These findings show that across several nutrients, adolescents consuming primarily egg dishes demonstrated lower rates of nutrient inadequacies compared with those who consumed eggs as ingredients and nonegg consumers.
Statistically higher TNI and FNI scores were observed among egg consumers compared with nonegg consumers, indicating an association between egg-consumption and overall micronutrient quality (Table 4). Adolescents consuming primarily egg dishes showed statistically higher (P < 0.001) total TNI scores (76 out of 100) when compared with those not consuming eggs (65 out of 100). Even those consuming eggs as ingredients in dishes showed statistically higher total TNI scores at 71 out of 100 when compared with 65 out of 100 for adolescents who did not consume eggs (P < 0.001). The total FNI score was statistically significantly higher (P < 0.001) among adolescents who consumed primarily egg dishes (75 out of 100) compared with adolescents who consumed eggs as ingredients in dishes (68 out of 100) and who were nonegg consumers (63 out of 100). Similarly, the TNI and FNI component scores of adolescents who consumed primarily egg dishes were significantly higher (P < 0.001) for magnesium, potassium, choline, folate, vitamin C, and vitamin D when compared with those who did not consume eggs at all (Table 4). Significantly higher TNI scores were also noted for adolescents who consumed eggs as ingredients in dishes in contrast with adolescents who were nonegg consumers for magnesium and potassium, and the same pattern was observed for the FNI but only for potassium. In addition, significantly higher TNI scores were noted for adolescents who consumed primarily egg dishes in comparison with adolescents who consumed eggs as ingredients in dishes for choline and in the FNI for vitamin D and choline.
TABLE 4.
Comparison of means of the Food Nutrient Index (FNI) and Total Nutrient Index (TNI) and component scores among US adolescents (14–17 y), by egg-consumption behavior, NHANES 2007–20181.
| TNI components | Nonegg consumers | Eggs as ingredients in dishes | Primarily egg dishes |
|---|---|---|---|
| Mean ±SE (n = 884) | Mean ±SE (n = 621) | Mean ±SE (n = 317) | |
| Calcium | 67.5 ±1.5 | 73.3 ± 1.3 | 74.2 ± 2.1 |
| Magnesium | 59.8 ±1.3ab | 65.9 ± 1.3a | 68.7 ± 1.8b |
| Potassium | 72.6 ±1.4ab | 79.6 ± 1.4a | 82.5 ± 1.8b |
| Zinc | 83.0 ±1.2 | 86.3 ±1.1 | 88.2 ± 1.4 |
| Choline | 49.4 ±1.2a | 53.5 ± 1.3b | 77.0 ± 1.9ab |
| Folate, DFE2 | 86.2 ± 1.2a | 91.1 ±1.0 | 91.6 ± 1.1a |
| Vitamin C | 67.7 ± 1.8a | 73.3 ± 2.0 | 79.6 ± 2.3a |
| Vitamin D | 36.2 ± 1.6a | 43.2 ± 2.1 | 49.7 ± 2.8a |
| Total TNI score | 65.3 ± 1.0ab | 70.6 ± 1.1a | 76.4 ±1.5b |
| FNI components | Nonegg consumers | Eggs as ingredients in dishes | Primarily egg dishes |
|---|---|---|---|
| Mean (SE) (n = 884) | Mean (SE) (n = 621) | Mean (SE) (n = 317) | |
| Calcium | 66.4 ± 1.5 | 72.0 ± 1.3 | 72.9 ± 2.1 |
| Magnesium | 58.8 ± 1.3a | 64.8 ± 1.3 | 67.6 ± 1.7a |
| Potassium | 72.5 ± 1.4ab | 79.5 ± 1.4a | 82.4 ± 1.8b |
| Zinc | 81.9 ± 1.2 | 84.7 ± 1.2 | 87.7 ± 1.5 |
| Choline | 49.4 ± 1.2a | 53.3 ± 1.3b | 76.9 ± 1.9ab |
| Folate, DFE2 | 84.9 ± 1.2a | 89.5 ± 1.1 | 91.2 ± 1.1a |
| Vitamin C | 63.5 ± 1.9a | 67.7 ± 2.1 | 75.8 ± 2.1a |
| Vitamin D | 29.2 ± 1.4a | 32.3 ± 1.2b | 41.7 ± 2.5ab |
| Total FNI score | 63.3 ± 1.0a | 68.0 ±1.0b | 74.5 ± 1.4ab |
A t-test was used with a P < 0.001 to account for multiple comparisons and the Bonferroni-adjusted P value was applied. The analysis involved the 3 egg-consumption groups, leading to 3 possible pairwise comparisons (3!/(3–2)!2=3). With 18 nutrient scores, this resulted in a total of 54 (3 by 18) comparisons, which were used in the Bonferroni adjustment, dividing 0.05 by 54 to obtain a P value of 0.001. The shared letter indicates significant differences between columns.
Abbreviations: DFE, dietary folate equivalents; FNI, food nutrient index; TNI, total nutrient index.
TNI/FNI scores were estimated using a simple algorithm method and NHANES day 1 dietary sampling weights were applied. Mean score (SE) out of a maximum score of 100.0.
Folate, as DFE.
Discussion
US adolescents’ usual mean intakes did not meet the nutrient requirements for several nutrients, including calcium, magnesium, vitamin D, and vitamin E, and mean usual choline intake was not above the AI. Adolescents classified in the eggs as ingredients and primarily egg dishes groups had higher mean usual intakes of several nutrients and a lower prevalence of intakes below the EAR and a higher proportion with intakes above the AI compared with nonegg consumers. These nutrient inadequacies may have current and long-term health and developmental implications for adolescents. It should be noted that there have been calls to reevaluate the EAR for vitamin E; although many individuals in the United States have low vitamin E intake, signs of deficiency are infrequently observed [46,47]. Adolescents consuming primarily egg dishes exhibited higher usual nutrient intake for lutein + zeaxanthin, choline, vitamin A, selenium, vitamin D, riboflavin, DHA, and protein when compared with the nonegg consumers; and for lutein + zeaxanthin, choline, selenium, and DHA when compared with adolescents consuming eggs as ingredients in dishes. Also, in the group consuming eggs as ingredients, higher intakes were observed for iron and vitamin E when compared with nonegg consumers. Adolescents who were nonegg consumers had a higher risk of nutrient inadequacy, whereas those consuming eggs, either as primarily dishes or as ingredients, had better nutrient adequacy, suggesting a positive association between egg consumption and overall nutrient adequacy. These results suggest egg consumption may function as a dietary marker associated with differences in nutrient intake profiles among US adolescents. The consumption of primarily egg dishes was associated with higher intakes of several key nutrients needed for growth and development during adolescence. Greater adherence to nutrient requirements even among those consuming eggs as ingredients compared with nonegg consumers further supports the presence of intake difference across egg-consumption categories. However, these findings should not be interpreted as evidence that inclusion of a single food is sufficient to address nutrient inadequacies where overall dietary patterns may be more important and egg-consumption may reflect broader differences in diet quality or food choice behaviors.
Overall, this study highlights differences in nutrient intake, nutrient adequacy, and exposure scores across egg consumption among US adolescents. A prior modeling analysis showed that adding 1 egg to breakfast among children and adolescents (1–18 y) into the Child and Adult Care Food Program led to an increase of 10% in usual intakes of pantothenic acid, riboflavin, selenium, and vitamin D compared with baseline values; and that the inclusion of 2 eggs resulted in a >10% increase in usual intakes of protein and vitamin A compared with baseline values [48]. Furthermore, the proportion of children above the AI for total choline increased to 44% and 58% with the addition of 1 and 2 eggs, respectively, compared with 23% at baseline [48]. Eggs contain a variety of essential nutrients (e.g., vitamins A, B-6, B-12, D, E; folate; thiamin; riboflavin; calcium; selenium; choline; zinc; iron; lutein and zeaxanthin; and omega-3 fatty acids DHA and α-linolenic acid) [7,49], which may partially explain the observed associations. Adolescent linear growth has the highest velocity after infancy, and growth and development during this time have profound impacts on health later in life, like adult height, muscle, fat mass, and risk of noncommunicable diseases [1]. A meta-analysis of interventional studies on egg supplementation for growth in children and adolescents (6 mo to 18 y) showed greater increases in height/length [by 0.47 (0.13, 0.80) cm, P < 0.01] and weight [by 0.07 (0.01, 0.13) kg, P = 0.03] when compared with those in the control groups (e.g., no egg supplement) [50]. However, interventional findings should be interpreted separately from the cross-sectional associations observed in the present study.
Despite the evidence demonstrating associations between egg intake and nutrient adequacy among children and adolescents [48,51,52] and their inclusion in evidence-based dietary patterns, like the Healthy US-Style Dietary Pattern [53], in this analysis, the percentage of adolescents consuming primarily egg dishes remained low. Dietary behaviors among adolescents do not occur in isolation but are influenced by multiple contextual factors. The food environment, which refers to the physical, economic, policy and cultural factors [54], influences adolescent’s food choices and diet quality [55]; therefore, dietary behaviors, including egg consumption, are influenced not only by individual choices but also by the availability and accessibility of nutritious foods in the environments at more macrolevel settings and policies. The school food environment influences adolescents’ food choices because they consume a substantial part of their total daily intake at school, for example, consuming both the school breakfast and lunch provides 47% of the students’ total daily energy intake that utilizes these programs [56]. The school breakfast and lunch programs are components of the school nutrition environment that impact students’ access to healthy foods at school [57].
The NSBP or NSLP provides nutritious meals and snacks at low or no cost to children and adolescents in participating schools [58]. Schools in these programs can qualify for federal meal reimbursements to support the cost of serving nutritious meals [59]. The NSBP or NSLP must offer foods within all food groups that align with guidelines as follows: fruits; vegetables, whole grains, meat/meat alternatives; fat-free or low-fat fluid milk; and meals that align with calorie ranges for each age/grade group [14]. Eggs may be offered within the NSBP as a meat/meat alternative component. Given their nutrient profile, their inclusion in NSBP could contribute to the overall nutrient composition of meals and may influence the balance of energy provided from different food sources, including foods higher in added sugars. Within the context of evolving nutrition standards aimed at gradually reducing added sugar in school meals [59], egg-containing options represent one example of how menu composition can affect overall nutrient energy distribution. Evidence from a modeling study showed that substituting 1 egg for another protein source in exemplary dietary patterns, including the Healthy US-Style, Harvard Medical School’s Healthy Eating Guide, the National Heart, Lung, and Blood Institute’s Dietary Approaches to Stop Hypertension, and the Healthy US-Style Vegetarian Dietary Pattern, improved nutrient adequacy for choline and vitamin D without raising overall costs [60]. Although the present study did not evaluate policy or intervention effects, these contextual findings help situate the observed associations within real-world dietary settings. Future research may further examine how egg-consumption categories relate to overall dietary patterns, food environment exposures, and longitudinal nutritional outcomes. Additionally, collaborations between policymakers, educators, healthcare professionals, and the food industry may influence the development and implementation of initiatives that shape adolescents’ dietary behaviors and their ability to meet dietary recommendations [54,55,61] including access to a variety of nutrient-dense foods.
A notable strength of this study is the utilization of data obtained from a nationally representative sample of US adolescents. Additionally, the combination of 6 survey cycles of NHANES data facilitated a sizable sample enabling the generation of reliable estimates. However, the sample size among primarily egg-consuming adolescents remained relatively small, which could have resulted in larger SEs and diminished ability to detect statistical significance. The NCI method was a strength as it accounted for random measurement errors inherent in 24-h recalls. However, it is important to note that the NCI method does not correct for systematic measurement error (e.g., underreporting or misreporting). Addressing systematic error would require the inclusion of recovery biomarkers, which were not aligned with the research aims. However, the cross-sectional design should be recognized as providing evidence of association and not causality. Using a single 24-h recall to estimate egg intake may lead to inaccuracies in reflecting daily egg consumption. Future analyses could incorporate multiple recalls to better capture habitual egg intake and reduce measurement error.
A potential limitation of this study is the possibility of misclassification of participants into the egg-consumption groups. Misclassification could occur in 3 ways: first, using a single day to classify egg consumers only represents their consumption on that day, not all days, second, participants may be classified as egg consumers (either primarily or through mixed dishes) even when the portion of egg consumed was small and not nutritionally meaningful; and third, some egg consumers may have been left out if eggs were part of a composite dish that was reported as a single item and not disaggregated into individual ingredients. Combination food entries were not individually reviewed in this study. Although disaggregated food codes generally allow for identification of eggs within mixed dishes, the risk of underclassification or overclassification remained. This limitation highlights the importance of improving dietary assessment methods to better capture foods consumed as part of mixed dishes. Future studies may also consider utilizing the Food Patterns Equivalents Database (FPED) for FPED-derived egg intake values as another indicator of egg consumption. Another limitation is that the analysis did not stratify results by sex; thus, sex-specific differences in nutrient requirements (e.g., iron) may have influenced inadequacy estimates. Consequently, the findings reflect population-level associations between eggconsumption categories and nutrient intake rather than sex-specific patterns. Future research may further explore whether these associations differ by sex in adolescent populations.
In conclusion, the majority of US adolescents failed to meet various micronutrient and protein recommendations, highlighting a high risk of inadequacy for nutrients such as calcium, magnesium, vitamin D, vitamin E, and a low proportion of adolescents with choline intakes above the AI. Those who consumed primarily egg dishes exhibited higher nutrient intakes for lutein + zeaxanthin, choline, vitamin A, selenium, vitamin D, riboflavin, DHA, and protein compared with nonegg consumers; and for lutein + zeaxanthin, choline, selenium, and DHA when compared with adolescents consuming eggs as ingredients in dishes. Adolescents who consumed eggs have a lower risk of nutrient inadequacy, and higher TNI and FNI scores when compared with nonegg consumers, highlighting that egg consumption, whether as primarily egg dishes or as ingredients in dishes, is associated with differences in nutrient intake. Understanding factors that influence accessibility and availability of nutrient-rich foods is imperative for interpreting dietary patterns and potential nutritional risks among United States adolescents.
Supplementary Material
Funding
This research was supported by the American Egg Board’s Egg Nutrition Center, Contract Number 22057732, and HAE-M received support from the Danone International Prize for Alimentation from the Danone Institute International Association and the French Medical Research Foundation.
Conflict of interest
HAE-M reports financial support was provided by American Egg Board. AEC-P reports a relationship with Journal of the Academy of Nutrition and Dietetics that includes: board membership. RLB reports a relationship with Nestle that includes: consulting or advisory. RLB reports a relationship with Think Health Group that includes: consulting or advisory. RLB reports a relationship with International Food Information Council that includes: board membership. RLB reports a relationship with American Journal of Nutrition that includes: board membership. HAE-M reports a relationship with the California Walnut Commission that includes: Scientific Advisory Board Membership. HAE-M reports a relationship with Journal of the Academy of Nutrition and Dietetics that includes: board membership. HAE-M reports a relationship with Advances in Nutrition that includes: board membership. HAE-M received support from the Danone International Prize from Alimentation from the Danone Institute International Association and the French Medical Research Foundation. RLB has received travel support to present her research on dietary supplements. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Abbreviations:
- AI
adequate intake
- DGA
Dietary Guidelines for Americans
- DS
dietary supplements
- DSMQ
Dietary Supplement and Prescription Medicine Questionnaire
- EAR
estimated average requirement
- FNDDS
Food and Nutrient Database for Dietary Studies
- FNI
Food Nutrient Index
- FPED
Food Patterns Equivalents Database
- MEC
mobile examination center
- NCI
National Cancer Institute
- NSBP
National School Breakfast Program
- NSLP
National School Lunch Program
- PIR
poverty-to-income ratio
- SP
sample person
- SNAP
Supplemental Nutrition Assistance Program
- TNI
total nutrient index
- WWEIA
What We Eat in America
Appendix A. Supplementary data
Supplementary data to this article can be found online at https://doi.org/10.1016/j.tjnut.2026.101483.
Footnotes
Declaration of generative AI and AI-assisted technologies in the writing process
The authors declare that no generative AI or AI-assisted technologies were used in the writing of this manuscript.
Data availability
Data described in the article and code book are publicly and freely available without restriction at https://www.cdc.gov/nchs/nhanes/index.htm. Analytic code will be made available upon request pending application and approval.
References
- [1].Norris SA, Frongillo EA, Black MM, Dong Y, Fall C, Lampl M, et al. , Nutrition in adolescent growth and development, Lancet. 399 (2022) 172–184. [DOI] [PubMed] [Google Scholar]
- [2].Bailey RL, Ard JD, Davis TA, Naimi TS, Schneeman BO, Stang JS, et al. , A proposed framework for identifying nutrients and food components of public health relevance in the Dietary Guidelines for Americans, J. Nutr 151 (2021) 1197–1204. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [3].U.S. Department of Agriculture and U.S. Department of Health and Human Services, Dietary guidelines for Americans-2020–2025 [Internet] [cited 21 July, 2025]. Available from: https://www.dietaryguidelines.gov/sites/default/files/2021-03/Dietary_Guidelines_for_Americans-2020-2025.pdf.
- [4].US Department of Agriculture, Agricultural Research Service: Dietary Guidelines Advisory Committee. Scientific report of the 2025 dietary guidelines advisory committee: advisory report to the Secretary of Health and Human Services and Agriculture and Secretary, Washington, DC, 2024. [Internet] [cited 21 August, 2025]. Available from: https://www.dietaryguidelines.gov/2025-advisory-committee-report. [Google Scholar]
- [5].Ziegler AM, Kasprzak CM, Mansouri TH, Gregory AM 2nd, Barich RA, Hatzinger LA, et al. , An ecological perspective of food choice and eating autonomy among adolescents, Front. Psychol 12 (2021) 654139. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [6].Eicher-Miller HA, Boushey CJ, Bailey RL, Yang YJ, Frequently consumed foods and energy contributions among food secure and insecure U.S. children and adolescents, Nutrients 12 (2) (2020) 304. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [7].Sebastian RS, Crawford SB, Moshfegh AJ, Consumption of eggs/omelets and egg sandwiches by U.S. children: what we eat in America, NHANES 2017 – March 2020, in: FSRG dietary data briefs, United States Department of Agriculture, USDA), 2025. [PubMed] [Google Scholar]
- [8].Egg cooking lessons [Internet] [cited 30 May, 2025]. Available from: https://www.incredibleegg.org/recipes/cooking-school/.
- [9].Das JK, Salam RA, Thornburg KL, Prentice AM, Campisi S, Lassi ZS, et al. , Nutrition in adolescents: physiology, metabolism, and nutritional needs, Ann. N. Y. Acad. Sci 1393 (1) (2017) 21–33. [DOI] [PubMed] [Google Scholar]
- [10].Rehault-Godbert S, Guyot N, Nys Y, The golden egg: nutritional value, bioactivities, and emerging benefits for human health, Nutrients 11 (3) (2019) 684. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [11].MyPlate Five Food Group Gallery [Internet] [cited 30 May, 2024]. Available from: https://www.myplate.gov/eat-healthy/food-group-gallery.
- [12].School Nutrition Programs—Healthier Kansas Menus—6-Week Breakfast Cycle [Internet] [cited 30 May, 2025]. Available from: https://cnw.ksde.org/snp/food-service-facts/chapters/chapter-16-menu-planning/healthier-kansas-menus/breakfast.
- [13].[Internet], Chapter 3 Menu Development, 2022. [cited 30 May, 2025]. Available from: https://www.fns.usda.gov/tn/menu-planner-school-meals.
- [14].Final Rule – Child Nutrition Programs: Meal Patterns Consistent With the 2020–2025 DGAs [Internet], 2024. [cited 23 May, 2025]. Available from: https://www.fns.usda.gov/cn/fr-042524.
- [15].Nutrition standards in the National School Lunch and School Breakfast Programs, Final rule [Internet] [cited 23 May, 2025]. Available from: https://pubmed.ncbi.nlm.nih.gov/22359796/. [PubMed]
- [16].Eicher-Miller HA, Zhao Y, Evidence for the age-specific relationship of food insecurity and key dietary outcomes among US children and adolescents, Nutr. Res. Rev 31 (1) (2018) 98–113. [DOI] [PubMed] [Google Scholar]
- [17].Morales-Juarez A, Cowan-Pyle AE, Bailey RL, Eicher-Miller HA, Eating egg-rich diets and modeling the addition of one daily egg reduced the risk of nutrient inadequacy among U.S. adolescents with and without food insecurity, J. Nutr 154 (2024) 3475–3484. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [18].National Health and Nutrition Examination Survey: plan and operations, 1999–2010, Vital Health Stat [Internet] 2013. [cited 23 June, 2025]. Available from: https://pubmed.ncbi.nlm.nih.gov/25078429/. [PubMed]
- [19].NHANES - NCHS Research Ethics Review Board Approval [Internet] [cited 23 June, 2025]. Available from: https://www.cdc.gov/nchs/nhanes/irba98.htm.
- [20].USDA, Child nutrition programs: income eligibility guidelines (2024–2025) [Internet] [cited 20 August, 2025]. Available from: https://www.fns.usda.gov/cn/fr-022024?utm_source=chatgpt.com.
- [21].Toossi S, Jones JW, The food and nutrition assistance landscape: fiscal year 2024 annual report, EIB-291 [Internet], U.S. Department of Agriculture, Economic Research Service, 2025. [cited 20 October, 2025]. 24 p. Available from: https://www.ers.usda.gov/publications/pub-details?pubid=112883. [Google Scholar]
- [22].SAS Program for CDC Growth Charts [Internet] [cited 6 October, 2024]. Available from: https://www.cdc.gov/growth-chart-training/hcp/computer-programs/sas.html?CDC_AAref_Val=https://www.cdc.gov/nccdphp/dnpao/growthcharts/resources/sas.htm.
- [23].Blanton CA, Moshfegh AJ, Baer DJ, Kretsch MJ, The USDA Automated Multiple-Pass Method accurately estimates group total energy and nutrient intake, J. Nutr 136 (10) (2006) 2594–2599. [DOI] [PubMed] [Google Scholar]
- [24].AMPM - USDA Automated Multiple-Pass Method : USDA ARS [Internet] [cited 6 March, 2025]. Available from: https://www.ars.usda.gov/northeast-area/beltsville-md-bhnrc/beltsville-humannutrition-research-center/food-surveys-research-group/docs/ampmusda-automated-multiple-pass-method/#what.
- [25].FNDDS download databases: USDA ARS [Internet] [cited 20 October, 2023]. Available from: https://www.ars.usda.gov/northeast-area/beltsville-md-bhnrc/beltsville-human-nutrition-research-center/foodsurveys-research-group/docs/fndds-download-databases/.
- [26].Gahche JJ, Bailey RL, Potischman N, Ershow AG, Herrick KA, Ahluwalia N, et al. , Federal monitoring of dietary supplement use in the resident, civilian, noninstitutionalized US population: National Health and Nutrition Examination Survey, J. Nutr 148 (2018) 1436S–1444S. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [27].Dietary supplement database: product information (DSPI), National Survey Health and Nutrition Examination, National Center for Health Statistics. [cited 25 May, 2024]. Available from: https://wwwn.cdc.gov/Nchs/Data/Nhanes/Public/1999/DataFiles/DSPI.htm.
- [28].Agricultural Research Service. What we eat in America Food Categories 2017-March 2020 Prepandemic [Internet] [cited 20 June, 2023]. Available from: https://www.ars.usda.gov/ARSUserFiles/80400530/pdf/1720/Food_Categories_2017-March%202020%20Prepandemic.pdf.
- [29].Jun S, Cowan AE, Dodd KW, Tooze JA, Gahche JJ, Eicher-Miller HA, et al. , Association of food insecurity with dietary intakes and nutritional biomarkers among US children, National Health and Nutrition Examination Survey (NHANES) 2011–2016, Am. J. Clin. Nutr 114 (3) (2021) 1059–1069. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [30].Cowan AE, Jun S, Tooze JA, Eicher-Miller HA, Dodd KW, Gahche JJ, et al. , Total usual micronutrient intakes compared to the dietary reference intakes among U.S. adults by food security status, Nutrients 12 (38) (2020) 38. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [31].Condon E, Drilea S, Jowers K, Lichtenstein C, Mabli J, Madden E, et al. , Diet Quality of Americans by SNAP Participation Status: data from the National Health and Nutrition Examination Survey, 2007–2010 [Internet]. 2015. [cited 7 September, 2024]. Available from: https://fns-prod.azureedge.us/sites/default/files/ops/NHANES-SNAP07-10.pdf. [Google Scholar]
- [32].Tooze JA, Midthune D, Dodd KW, Freedman LS, Krebs-Smith SM, Subar AF, et al. , A new statistical method for estimating the usual intake of episodically consumed foods with application to their distribution, J. Am. Diet. Assoc 106 (10) (2006) 1575–1587. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [33].National Academies of Sciences, Engineering, and Medicine, Dietary reference intakes for sodium and potassium, The National Academies Press, Washington, DC, 2019, pp. 578–579. [PubMed] [Google Scholar]
- [34].Institute of Medicine (US), Dietary reference intakes for calcium and vitamin D, The National Academies Press, Washington, DC, 2011, pp. 1116–1117. [PubMed] [Google Scholar]
- [35].Institute of Medicine (US), Panel on Dietary Antioxidants and Related Compounds, Dietary reference intakes for vitamin C, vitamin E, selenium, and carotenoids, The National Academies Press, Washington, DC, 2000, pp. 506–507. [PubMed] [Google Scholar]
- [36].Institute of Medicine (US), Dietary reference intakes for vitamin A, vitamin K, arsenic, boron, chromium, copper, iodine, iron, manganese, molybdenum, nickel, silicon, vanadium, and zinc, The National Academies Press, Washington, DC, 2001, pp. 773–774. [PubMed] [Google Scholar]
- [37].Institute of Medicine (US) Standing Committee on the Scientific Evaluation of Dietary Reference Intakes, Dietary reference intakes for calcium, phosphorus, magnesium, vitamin D, and fluoride, The National Academies Press, Washington, DC, 1997, pp. 432–433. [PubMed] [Google Scholar]
- [38].Institute of Medicine (US), Dietary reference intakes for thiamin, riboflavin, niacin, vitamin B6, folate, vitamin B12, pantothenic acid, biotin, and choline, The National Academies Press, Washington, DC, 1998, pp. 567–568. [PubMed] [Google Scholar]
- [39].Institute of Medicine (US), Dietary reference intakes for energy, carbohydrate, fiber, fat, fatty acids, cholesterol, protein and amino acids, The National Academies Press, Washington, DC, 2005, p. 1332. [Google Scholar]
- [40].Institute of Medicine (US), Subcommittee on Interpretation and Uses of Dietary Reference Intakes; Institute of Medicine (US) Standing Committee on the Scientific Evaluation of Dietary Reference Intakes: applications in dietary assessment, The National Academies Press, Washington, DC, 2000, pp. 289–290. [PubMed] [Google Scholar]
- [41].Rao JNK, Shao J, Modified balanced repeated replication for complex survey data, Biometrika 86 (2) (1999) 403–415. [Google Scholar]
- [42].Burt VL, Cohen SB, A comparison of methods to approximate standard errors for complex survey data, Rev. Public Data Use 12 (3) (1984) 159–168. [PubMed] [Google Scholar]
- [43].Cowan AE, Jun S, Tooze JA, Dodd KW, Gahche JJ, Eicher-Miller HA, et al. , A narrative review of nutrient based indexes to assess diet quality and the proposed total nutrient index that reflects total dietary exposures, Crit. Rev. Food Sci. Nutr 63 (12) (2023) 1722–1732. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [44].Cowan AE, Bailey RL, Jun S, Dodd KW, Gahche JJ, Eicher-Miller HA, et al. , The total nutrient index is a useful measure for assessing total micronutrient exposures among US adults, J. Nutr 152 (3) (2022) 863–871. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [45].Centers for Disease Control and Prevention, National Center for Health Statistics, Dietary interview–total nutrient intakes, first day 2007–2018 (DR1TOT) [Internet] [cited 15 October, 2025]. Available from: https://wwwn.cdc.gov/nchs/nhanes/search/datapage.aspx?%20Component%C2%BCDietary&CycleBeg.
- [46].MacFarlane AJ, Cogswell ME, De Jesus JM, Greene-Finestone LS, Klurfeld DM, Lynch CJ, et al. , A report of activities related to the Dietary Reference Intakes from the Joint Canada-US Dietary Reference Intakes Working Group, Am. J. Clin. Nutr 109 (2) (2019) 251–259. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [47].Traber MG, Vitamin E inadequacy in humans: causes and consequences, Adv. Nutr 5 (5) (2014) 503–514. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [48].Papanikolaou Y, Fulgoni VL, Increasing egg consumption at breakfast is associated with increased usual nutrient intakes: a modeling analysis using NHANES and the USDA Child and Adult Care Food Program school breakfast guidelines, Nutrients 13 (4) (2021) 1379. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [49].Full Nutrition Facts for 1 Large Egg (50 g) [Internet] [cited 8 June, 2024]. Available from: https://www.incredibleegg.org/wp-content/uploads/2023/07/large-vertical.pdf.
- [50].Larson EA, Zhao Z, Bader-Larsen KS, Magkos F, Egg consumption and growth in children: a meta-analysis of interventional trials, Front. Nutr 10 (2024) 1278753. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [51].Papanikolaou Y, Fulgoni VL, Egg consumption in US children is associated with greater daily nutrient intakes, including protein, lutein + zeaxanthin, choline, α-linolenic acid, and docosahexanoic acid, Nutrients 11 (2019) 1137. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [52].Papanikolaou Y, Fulgoni VL, Modeling the removal and addition of eggs in the current US diet is linked to choline and lutein + zeaxanthin usual intakes in childhood, Curr. Dev. Nutr 5 (2020) nzaa181. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [53].Sample Menus for a 2000 Calorie Food Pattern, 2010. [cited 12 September, 2023]. Available from: https://search.nal.usda.gov.
- [54].Swinburn B, Sacks G, Vandevijvere S, Kumanyika S, Lobstein T, Neal B, et al. , INFORMAS (International Network for Food and Obesity/non-communicable diseases Research, Monitoring and Action Support): overview and key principles, Obes. Rev 14 (Suppl 1) (2013) 1–12. [DOI] [PubMed] [Google Scholar]
- [55].Story M, Neumark-Sztainer D, French S, Individual and environmental influences on adolescent eating behaviors, J. Am. Diet. Assoc 102 (3 Suppl) (2002) S40–S51. [DOI] [PubMed] [Google Scholar]
- [56].Cullen KW, Chen TA, The contribution of the USDA school breakfast and lunch program meals to student daily dietary intake, Prev. Med. Rep 5 (2017) 82–85. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [57].Comprehensive Framework for Addressing the School Nutrition Environment and Services [Internet], 2019. [cited 8 June, 2024]. Available from: https://www.cdc.gov/healthyschools/nutrition/pdf/School_Nutrition_Framework_508tagged.pdf.
- [58].Food and Nutrition Service, U.S. Department of Agriculture. Updated Offer vs Serve Guidance for the NSLP and SBP Beginning SY2015–16, 2015. [Internet]. [cited 5 June, 2024]. Available from: https://www.fns.usda.gov/cn/updated-offer-vs-serve-guidance-nslp-and-sbp-beginning-sy2015-16.
- [59].U.S. Department of Agriculture, Biden-Harris Administration Announces new school meal standards to strengthen child nutrition, 2024. [cited 5 June, 2024]. Available from: https://www.usda.gov/media/press-releases/2024/04/24/biden-harris-administration-announces-new-school-meal-standards.
- [60].Morales-Juarez A, Cowan-Pyle AE, Bailey RL, Eicher-Miller HA, Modeling the substitution of one egg increased the nutrient quality of choline and vitamin D in exemplary menus, Nutrients 17 (7) (2025) 1129. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [61].Downs SM, Ahmed S, Fanzo J, Herforth A, Food environment typology: advancing an expanded definition, framework, and methodological approach for improved characterization of wild, cultivated, and built food environments toward sustainable diets, Foods 9 (2020) 532. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
Data described in the article and code book are publicly and freely available without restriction at https://www.cdc.gov/nchs/nhanes/index.htm. Analytic code will be made available upon request pending application and approval.