Background/objectives: Adolescence is a critical period for both the development of overweight and the transition toward a later chronotype, often accompanied by an increase in social jetlag. This study assessed whether changes in chronotype and social jetlag, are linked to changes in body composition during adolescence. Subjects/methods: We used data from the DONALD open cohort study, collected between 2014 and 2019, from 213 adolescents (9–17 years at baseline, 45% females) having at least two measures of chronotype and anthropometry (N = 572). Chronotype was assessed with the Munich Chronotype Questionnaire and defined as: midpoint of sleep corrected for sleep-debt (MSFsc) accumulated over the week (later MSFsc represents later chronotype). Social jetlag (SJL) defines the difference between midpoint of sleep during week and weekend. Calculations for Fat Free Mass Index (FFMI [kg/m²)]) and Fat Mass Index (FMI) [kg/m²)]) were based on body fat percentage, weight, and height. To analyze the associations, we used linear mixed-effect regression models. Finally, the total cohort was split into three biologically relevant age groups (cut-off set at 15 years). Results: Median follow-up was 2.1 years. Overall, change toward a later chronotype was significantly related with an increase in FMI (ß: 0.05, 95% CI: 0.01–0.08). A 1 h increase in social jetlag predicted an increase in BMI-SDS of 0.08 SDS units (95% CI: 0.01–0.14) and in FMI of 0.04 kg/m2 (95% CI: 0.003–0.08). Associations were stronger for the age group ≥12 to ≤15 years (p for interaction: <0.001). No relationship was found with FFMI. Conclusions: Changes in MSFsc and SJL during adolescence were associated with concurrent changes in BMI-SDS and FMI. The age ≥12 to ≤15 years appears to be a sensitive period in which chronobiological changes were clearly associated with increasing body fatness.

The COVID-19 pandemic may have changed the habitual lifestyles of children and adolescents, in particular, due to the closure of kindergartens and schools. To investigate the impact of the pandemic on nutrients and food intake of children and adolescents in Germany, we analyzed repeated 3-day weighed dietary records from 108 participants (3–18 years; females: n = 45, males: n = 63) of the Dortmund Nutritional and Anthropometric Longitudinally Designed (DONALD) study. Polynomial mixed-effects regression models were used to identify prospective changes in dietary intake (total energy (TEI), carbohydrates, fat, protein, free sugar, ultra-processed foods, fruits and vegetables, sugar sweetened beverages and juices) before and during the first months of the COVID-19 pandemic. For the current analysis, we have chosen the first months of the pandemic (March 2020–August 2020), as this was the period with the most restrictions in Germany so far (kindergarten, school and restaurant closures; contact and outdoor activity restrictions). No significant changes in either the selected nutrients or food groups were observed. However, children and adolescents recorded a significantly lower TEI during the pandemic (β = −109.65, p = 0.0062). Results remained significant after the exclusion of participants with under-reported records (β = −95.77, p = 0.0063). While macronutrient intake did not change, descriptive data indicate a non-significant decrease in sugar sweetened beverages and ultra-processed foods intake. We suggest that children and adolescents from high socioeconomic families may have adapted lifestyle changes during the pandemic.

Purpose: Glycemic response to the same meal depends on daytime and alignment of consumption with the inner clock, which has not been examined by individual chronotype yet. This study examined whether the 2-h postprandial and 24-h glycemic response to a meal with high glycemic index (GI) differ when consumed early or late in the day among students with early or late chronotype. Methods: From a screening of 327 students aged 18–25 years, those with early (n = 22) or late (n = 23) chronotype participated in a 7-day randomized controlled cross-over intervention study. After a 3-day observational phase, standardized meals were provided on run-in/washout (days 4 and 6) and intervention (days 5 and 7), on which participants received a high GI meal (GI = 72) in the morning (7 a.m.) or in the evening (8 p.m.). All other meals had a medium GI. Continuous glucose monitoring was used to measure 2-h postprandial and 24-h glycemic responses and their variability. Results: Among students with early chronotype 2-h postprandial glucose responses to the high GI meal were higher in the evening than in the morning (iAUC: 234 (± 92) vs. 195 (± 91) (mmol/L) × min, p = 0.042). Likewise, mean and lowest 2-h postprandial glucose values were higher when the high GI meal was consumed in the evening (p < 0.001; p = 0.017). 24-h glycemic responses were similar irrespective of meal time. Participants with late chronotype consuming a high GI meal in the morning or evening showed similar 2-h postprandial (iAUC: 211 (± 110) vs. 207 (± 95) (mmol/L) × min, p = 0.9) and 24-h glycemic responses at both daytimes. Conclusions: Diurnal differences in response to a high GI meal are confined to those young adults with early chronotype, whilst those with a late chronotype seem vulnerable to both very early and late high GI meals. Registered at clinicaltrials.gov (NCT04298645; 22/01/2020).

Purpose: To analyse the association between intake of total dairy (TD) and types of dairy [liquid dairy (LD), solid dairy (SD), low-fat dairy (LFD), high-fat dairy (HFD), high sugar dairy (HSD), low-sugar dairy (LSD), not fermented dairy (NFD), as well as fermented dairy (FD)] and long-term changes in body weight status and composition among children and adolescents in Germany. Methods: In total, 9999 3-day dietary records collected between 1985 and 2019 by 1126 participants (3.5–18.5 years; boys: 50.8%) of the Dortmund Nutritional and Anthropometric Longitudinally Designed (DONALD) study were analysed. Polynomial mixed-effects regression models were used to examine whether changes (median follow-up: 9 years) in the intake of TD and dairy types (in 100 g/1000 kcal total energy intake) were associated with changes in body-mass-index-standard-deviation-score (BMI-SDS); fat mass index (FMI); fat-free mass index (FFMI) over time. Results: An individual increase in TD intake was slightly but significantly associated with an increase in BMI-SDS (β = 0.0092; p = 0.0371), FMI (β = 0.022; p = 0.0162), and FFMI (β = 0.0156; p = 0.0417) after adjustment for potential confounder. Analyses for LD (BMI-SDS: β = 0.0139; p = 0.0052; FMI: β = 0.0258; p = 0.0125; FFMI: β = 0.0239; p = 0.0052) and LSD intake (BMI-SDS: β = 0.0132; p = 0.0041, FMI: β = 0.02; p = 0.0316, FFMI: β = 0.0183; p = 0.0189) showed similar results to TD. Both processing method and fat content showed no association with body composition in our analyses. Conclusion: Increases in TD, LD, and LSD intake showed small but significant increases in BMI and concomitant increases in fat mass and lean mass. However, the observed changes were too small to expect biological or physiological meaningful effects. Overall, our results showed that policies to promote dairy intake in childhood are to be welcomed, as no negative effects on body composition are expected, while the intake of important nutrients for growth is ensured. The type of dairy does not seem to matter.

Purpose: Our aim was to assess alignment in timing of ‘highest caloric intake’ with individual chronotype and its association with body composition in adolescents. Methods: We used repeatedly collected data from n = 196 adolescents (age 9–16 years, providing N = 401 yearly questionnaires) of the DONALD open cohort study. Chronotype was assessed by the Munich Chronotype Questionnaire from which midpoint of sleep (MSFsc) was derived. A sex- and age-specific diet-chrono-alignment score (DCAS) was calculated as the difference in hours between the chronotype-specific median timing of highest caloric intake of the studied population and the individual timing of ‘highest caloric intake’ or vice versa. Repeated-measures regression models were applied to study cross-sectional and longitudinal associations between the DCAS and body composition, e.g., Fat Mass Index (FMI) or Fat Free Mass Index (FFMI). Results: DCAS ranged from −6:42 h to + 8:01 h and was not associated with body composition. Among adolescents with a later chronotype (N = 201) a 1 h increase in DCAS (later consumption of ‘highest caloric intake’ in comparison to the median intake of that group), increased FFMI by 1.92 kg/m² (95% CI: 0.15, 3.69, p value = 0.04) over a median follow-up of 0.94 year. Conclusion: Alignment of energy intake with individual chronotype appears beneficial for FFMI among those with a late chronotype.

OBJECTIVE:The aim of this analysis was to investigate whether habitual intake of total dairy (TD) or different dairy types (liquid, solid, fermented, not-fermented, low-fat, high-fat, low-sugar and high-sugar dairy) during adolescence is associated with biomarkers of low-grade inflammation as well as risk factors of type 2 diabetes in young adulthood.DESIGN:Multivariable linear regression analyses were used to investigate prospective associations between estimated TD intake as well as intake of different types of dairy and a pro-inflammatory score, based on hsCRP, IL-6, IL-18, leptin and adiponectin, and insulin resistance assessed as HOMA2-IR in an open cohort study.SETTING:Dortmund, GermanyPARTICIPANTS:Data from participants (n=375) of the DOrtmund Nutritional and Anthropometric Longitudinally Designed (DONALD) study were included, for whom at least two 3-day weighed dietary records during adolescence (median age: 11 years) and one blood sample in young adulthood (>18 years) were available.RESULTS:There was no statistically significant association between TD intake or intake of any dairy type and the pro-inflammatory score (all p>0.05). TD intake as well as each dairy type intake and insulin resistance also showed no association (all p>0.05).CONCLUSIONS:The habitual intake of dairy or individual types of dairy during adolescence does not seem to have a major impact on low-grade systemic inflammation and insulin resistance in the long term. There was no indication regarding a restriction of dairy intake for healthy children and adolescents in terms of diabetes risk reduction.