There is a lack of data on associations between modern vegetarian and vegan diets and health among children and adolescents. The aim of the Vechi Youth Study was to cross-sectionally examine anthropometry, dietary intakes and nutritional status in a sample of 149 vegetarian, 115 vegan and 137 omnivore children and adolescents (6–18 years old, mean age: 12.7 ± 3.9 years). Group differences of dietary intake (calculated from three-day dietary records), nutrient biomarker and blood lipid concentrations were assessed using an analysis of covariance, adjusted for sex, age and other covariates. The total energy intake did not differ significantly between groups, but intake of carbohydrates was higher among vegetarians and vegans than among omnivores (p = 0.0002, respectively). The median protein intake exceeded 0.9 g/kg body weight/day in all diet groups and was lowest among vegetarians (p < 0.02). There was no significant difference of haemoglobin, vitamin B2, 25-OH vitamin D3, HDL-C and triglycerides blood concentrations between diet groups. Vegan participants had higher folate concentrations than vegetarian participants (p = 0.0053). Ferritin concentration was significantly higher in omnivores than in vegetarians (p = 0.0134) and vegans (p = 0.0404). Vegetarians had lower concentrations of holotranscobalamin (p = 0.0042) and higher concentrations of methylmalonic acid (p = 0.0253) than omnivores. Vegans had the lowest non-HDL-C and LDL-C concentrations in comparison to vegetarians (p = 0.0053 and p = 0.0041) and omnivores (p = 0.0010 and p = 0.0010). A high prevalence (>30%) of 25-OH vitamin D3 and vitamin B2 concentrations below reference values were found irrespective of the diet group. In conclusion, the Vechi Youth Study did not indicate specific nutritional risks among vegetarian and vegan children and adolescents compared to omnivores.

Objective: Although breakfast is important for obesity prevention and dietary quality, breakfast skipping is a common behaviour. Knowledge of changes in breakfast habits may provide potential behaviour targets for intervention programmes. The present study describes the actual data on trends in breakfast habits and composition.Design: A total of 7800 3 d dietary records of 1081 participants aged 2–18 years collected between 1986 and 2007 in the DONALD (Dortmund Nutritional and Anthropometric Longitudinally Designed) Study were analysed using mixed linear models.Results: Breakfast was eaten at 78 % of all record days; regular breakfast (breakfast was eaten on all three recorded weekdays) was eaten in 75 % of records. During the study period, the number of records with regular breakfast decreased significantly in 6–12- and 13–18-year-olds (P= 0·0084 and 0·0350, respectively). Of all breakfast meals, 62 % were bread meals and 21 % were ready-to-eat cereal (RTEC) meals. RTEC meals nearly doubled from the youngest to the oldest age group (P< 0·0001). During the study period, the percentage of bread meals decreased, whereas the percentage of RTEC meals increased (P< 0·0001). A higher percentage of RTEC meals than the bread meals was in accordance with the food-based guidelines (36 %v. 20 %,P< 0·0001), i.e. a breakfast including grain, dairy and fruit/vegetables.Conclusions: In the DONALD Study sample, a negative age and time trend in breakfast consumption was verified. Interventions regarding breakfast habits should be aimed at adolescents and should focus on fruit/vegetables.

The DONALD study (Dortmund Nutritional and Anthropometric Longitudinally Designed study) gives the opportunity to evaluate long-term food and nutrient intake data on the basis of 3 d weighed dietary records of infants, children and adolescents since 1985. In this paper, we examine changes in energy and macronutrient intakes (protein, fat, saturated, mono- and polyunsaturated fatty acids, carbohydrates and added sugars) of 795 2–18-year-old subjects between 1985 and 2000 (4483 records). No significant changes in intakes of energy and of protein, polyunsaturated fatty acids and added sugars (as % energy intake, E %) were found. Fat intake decreased significantly in all age groups (between -0·20 and -0·26 E %/year), as well as intake of saturated fatty acids (between -0·11 and -0·14 E %/year) and monounsaturated fatty acids (between -0·07 and -0·014 E %/year). This decline was compensated for by a significant increase in carbohydrate intake (between +0·18 and +0·27 E %/year). The changes in macronutrient intake were mainly due to a decreased consumption of fats–oils (between -0·29 and -1·26 g/year) and meat–fish–eggs (between -0·21 and -2·92 g/year), whereas consumption of bread–cereals (between +0·12 and +2·42 g/year) and potatoes–pasta–rice (between +0·15 and +2·26 g/year) increased slightly. However, since recommended fat intake and fatty acid composition was not reached at the end of the study period by far, further efforts will be necessary to improve macronutrient composition and to stabilize favourable dietary habits.

Due to the lack of current, large-scale studies examining their dietary intake and health, there are concerns about vegetarian (VG) and vegan (VN) diets in childhood. Therefore, the Vegetarian and Vegan Children Study (VeChi Diet Study) examined the energy and macronutrient intake as well as the anthropometrics of 430 VG, VN, and omnivorous (OM) children (1–3 years) in Germany. A 3-day weighed dietary record assessed dietary intake, and an online questionnaire assessed lifestyle, body weight (BW), and height. Average dietary intakes and anthropometrics were compared between groups using ANCOVA. There were no significant differences in energy intake or density and anthropometrics between the study groups. OM children had the highest adjusted median intakes of protein (OM: 2.7, VG: 2.3, VN: 2.4 g/kg BW, p < 0.0001), fat (OM: 36.0, VG: 33.5, VN: 31.2%E, p < 0.0001), and added sugars (OM: 5.3, VG: 4.5, VN: 3.8%E, p = 0.002), whereas VN children had the highest adjusted intakes of carbohydrates (OM: 50.1, VG: 54.1, VN: 56.2%E, p < 0.0001) and fiber (OM: 12.2, VG: 16.5, VN: 21.8 g/1,000 kcal, p < 0.0001). Therefore, a VG and VN diet in early childhood can provide the same amount of energy and macronutrients, leading to a normal growth in comparison to OM children.

During adolescence, a shift from morningness to eveningness occurs, yet school continues to start early in the morning. Hence, adolescents are at risk for social jetlag, i.e. a discrepancy between biological and social timing. It remains to be determined whether chronotype associates with daily and daytime-specific eating patterns during this potentially critical period. Therefore, the aim of the present study was to investigate whether chronotype is decisive for daily eating patterns [total energy intake (TEI, kcal), total macronutrient intake (% of TEI), eating occasion frequency (n/day), meal frequency (n/day), snack frequency (n/day), duration of nightly fasting], or daytime-specific eating patterns [morning (before 11 am) energy intake (% of TEI), morning macronutrient intake (% of morning energy intake), regular breakfast skipping (no morning energy intake at least on 2 of 3 days, yes/no), evening (after 6 pm) energy intake (% of TEI), evening macronutrient intake (% of evening energy intake), regular dinner skipping (no evening energy intake at least on 2 of 3 days, yes/no)] in German adolescents. Chronotype was assessed by use of the Munich Chronotype Questionnaire and is defined as the midpoint of sleep corrected for sleep-debt accumulated over the workweek (the later the midpoint of sleep, the later the chronotype). A total of 223 participants (10–18 years) provided 346 questionnaires and concurrent 3-day weighed dietary records. Associations between chronotype and eating patterns were analyzed cross-sectionally using multivariable linear and logistic mixed-effects regression models. Adolescents with earlier and later chronotypes did not differ in their daily eating patterns. With respect to daytime-specific eating patterns, 1 h delay in chronotype was associated with 4.0 (95% CI 2.5–6.6) greater odds of regular breakfast skipping (p < 0.0001). In addition, later chronotype was associated with higher evening energy intake (p = 0.0009). In conclusion, our data show that a later chronotype among adolescents is associated with a shift of food consumption toward later times of the day. Hence, adolescents’ eating patterns appear to follow their internal clock rather than socially determined schedules.