BackgroundDiets of U.S. adolescents and adults do not meet recommendations, increasing risk of chronic disease. This study examined trajectories and predictors of eating behaviors in U.S. youth from age 16–20 years, and evaluated longitudinal associations of eating behaviors with weight outcomes.MethodsData come from the first four waves (years) of the NEXT Generation Health Study, a nationally representative cohort of U.S. students in 10th grade during the 2009–2010 school year (n = 2785). Annual surveys queried frequency of food group intake (times/day of fruit and vegetables, whole grains, sugar-sweetened soda, sweet and salty snacks), and meal practices (days/week of breakfast, family meals, fast food, and television during meals). Body mass index (BMI, kg/m2) was calculated from self-reported height and weight. Adjusted generalized estimating equations and linear mixed models with multiple imputation for missing data estimated eating behavior trajectories overall and by baseline weight status (normal weight = 5 ≤ BMI%ile < 85, overweight = 85 ≤ BMI%ile < 95, obese = BMI%ile ≥ 95), accounting for the complex sampling design. Separate GEE models estimated longitudinal associations of food group frequencies with meal practices and of BMI with eating behaviors.ResultsEating behaviors tracked strongly from wave 1–4 (residual intraclass correlation = 41 % - 51 %). Across all baseline weight categories, frequency of food group intake and meal practices decreased over time, except for fast food, which remained stable. Fruit/vegetable intake frequency was associated positively with family meals (β ± SE = 0.33 ± 0.05) and breakfast (0.18 ± 0.03), and inversely with fast food (−0.31 ± 0.04), while whole grain intake frequency was associated positively with family meals (0.07 ± 0.02), television meals (0.02 ± 0.009) and breakfast (0.04 ± 0.01). Soda and snacks were positively associated with television meals (0.08 ± 0.008 and 0.07 ± 0.009, respectively) and fast food (0.24 ± 0.02 and 0.20 ± 0.03, respectively), while soda was inversely associated with breakfast frequency (−0.05 ± 0.01). Time-varying BMI was unrelated to eating behaviors other than an inverse association with time-varying snacks (−0.33 ± 0.12).ConclusionsStrong tracking over time supports the importance of early establishment of health-promoting eating behaviors in U.S. adolescents. Findings suggest meal practices may be important intervention targets. Lack of evidence for hypothesized associations of BMI and eating behaviors indicates the need for research confirming these findings using more precise measures of dietary intake.Electronic supplementary materialThe online version of this article (doi:10.1186/s12966-015-0298-x) contains supplementary material, which is available to authorized users.

BackgroundYouth’s physical activity (PA) may change across developmental periods. Although previous studies have observed a decline in levels of PA during adolescence, few studies have explored trends in PA during the transition from adolescence to young adulthood and what factors may impact the transitional change. The purpose of this study was to examine changes and predictors of change over time in PA from 10th grade to post-high school.MethodsThe NEXT Generation Health Study recruited a nationally-representative cohort of US 10th-graders, and administered longitudinal surveys in four waves (years) to follow up the participants to their first year after high school. Using transition models, the self-reported outcomes, moderate-to-vigorous PA (MVPA) and vigorous PA (VPA) each of which was repeatedly measured by one question, were modelled in association with wave-4 environmental-status variables and time-varying covariates.ResultsThere was a continuous decline in the proportion of respondents who met or exceeded the minimum recommended level for either MVPA (from 55.97 to 34.33 %) or VPA (from 65.96 to 54.90 %) from W1 to W4. Higher scores of peer PA, family support and VPA planning were prospectively associated with higher likelihood of meeting the MVPA/VPA recommendations. At wave 4, compared to those not working, attending 4-year colleges, or living on campus, participants working full/part time, not attending school or attending community-college level schools, and living at home or in own place were more likely to engage in MVPA.ConclusionsPeer PA, family support, self-regulatory skills, and environmental status after high school are critical factors that can promote MVPA/VPA among adolescents and emerging adults.

Excess adiposity is associated with increased cardiovascular risk factors in this sample of youth with type 1 diabetes. Non-significant associations with adiponectin and 8-iso-PGF2α suggest potential differences from the general population in the role of adiposity in cardiovascular health.

Introduction Driving while impaired (DWI) increases the risk of a motor vehicle crash by impairing performance. Few studies have examined the prevalence and predictors of marijuana, alcohol, and drug specific DWI among emerging adults. Methods The data from wave 3 (W3, high-school seniors, 2012, N=2407) and wave 4 (W4, one year after high school, N=2178) of the NEXT Generation Health Study with a nationally-representative cohort. W4 DWI (≥1 day of past 30 days) was specified for alcohol-specific, marijuana-specific, alcohol/marijuana-combined, illicit drug-related DWI. Multinomial logistic regression models estimated the association of W4 DWI with W3 covariates (perceived peer/parent influence, drinking/binge drinking, marijuana/illicit drug use), and W4 environmental-status variables (work/school/residence) adjusting for W3 overall DWI, demographic and complex-survey variables. Results Overall DWI prevalence from W3 to W4 changed slightly (14% to 15%). W4 DWI consisted of 4.34% drinking-specific, 5.02% marijuana-specific, 2.41% drinking/marijuana-combined, and 3.37% illicit drug-related DWI. W3 DWI was significantly associated with W4 alcohol-related and alcohol/marijuana-combined DWI, but not other DWI. W3 marijuana use, binge drinking, and illicit drug use were positively associated with W4 marijuana-specific, alcohol/marijuana-combined, and illicit drug-related DWI respectively. W3 friend drunkenness and marijuana use were positively associated with W4 alcohol-specific and marijuana-related DWI respectively. W3 peer marijuana use was negatively associated with W4 alcohol-specific DWI. Conclusions Driving under the influence of alcohol, marijuana, and illicit drugs is a persistent, threatening public health concern among emerging US adults. High-school seniors’ binge drinking as well as regular alcohol drinking and marijuana/illicit drug use were independently associated with respective DWI one year after high school. Peer drunkenness and marijuana use in high school may be related to subsequent DWI of emerging adults. Practical applications The results support the use of injunctive peer norms about getting drunk and smoking marijuana in guiding the development of prevention programs to reduce youth DWI.

Aims: The impact of adiposity on glycemic control in type 1 diabetes patients has important implications for preventing complications. This study examined associations of glycemic outcomes with body mass index (BMI, kg/m2) and body composition in youth with type 1 diabetes. Methods: This is a secondary analysis of an 18-month randomized controlled dietary intervention trial (N = 136, baseline age = 12.3 ± 2.5 y, HbA1c = 8.1 ± 1.0% (65 ± 11 mmol/mol)). Measured height and weight every 3 months were abstracted from medical records. Body composition was assessed by dual energy X-ray absorptiometry (DXA) at baseline, 12 and 18 months. Glycated hemoglobin (HbA1c) and glycemic variability assessed by masked 3-day continuous blood glucose monitoring (CGM) were obtained every 3 months. 1,5-Anhydroglucitol (1,5-AG) was assessed every 6 months. Adjusted random effects models for repeated measures estimated associations of time-varying BMI and body composition with time-varying glycemic outcomes. Results: There was no treatment effect on glycemic outcomes. HbA1c was not associated with BMI or body composition indicators. 1,5-AG was inversely associated with BMI and adiposity indicators (%fat, trunk fat mass and trunk %fat), adjusting for developmental covariates. Adiposity indicators were positively associated with %glucose >180 mg/dL and >126 mg/dL when adjusting for developmental covariates, and %glucose >126 mg/dL when additionally adjusting for diabetes-related covariates. Fewer consistent relationships were observed for 3-day mean glucose and %glucose <70.2 mg/dL. BMI and body composition variables were not associated with standard deviation of glycemic values or mean amplitude of glycemic excursions. Conclusions: The role of greater BMI and adiposity in diabetes management in youth with type 1 diabetes may relate specifically to increased hyperglycemic excursions.