Poor academic performance has been linked to factors such as sleep, health, illicit drug use, physical fighting, social media use, cyber bullying, physical activity, homelessness, times spent in video games and television. It is difficult to get a sense of the interplay between and relative importance of different behaviours/factors on academic performance as only limited research has been aimed at quantifying these factors.

To evaluate association of school performance and variables in five categories of the YRBSS: physical fighting, diet/lifestyle, electronic device usage, concurrent substance use, and violence/self-harm.

The CDC Youth Risk Behavior Surveillance System (YRBSS) data from 1991-2019 was used in study. Respondents were grouped by good and poor school performance and variables related to nutrition/lifestyle, electronic device use, concurrent substance use, mood/violence/self-harm were analyzed using chi-square test.

A total of 41,235 student respondents.Nutrition/Lifestyle, electronic device use, concurrent substance use, mood/violence/self-harm are found to be significantly correlated with school performance.

In national data, we found school performance is affected by nutrition, lifestyle, substance use, mood and exposure to surrounding violence, and self-harm. Further studies should be planned to evaluate benefits from the risk stratification to reduce this burden amongst US adolescents.

No significant relationships.

With the intention to inform future public health initiatives, we aimed to determine the extent to which typical childhood dietary trajectories predict adolescent cardiovascular phenotypes.

Longitudinal study. Exposure was determined by a 4 d food diary repeated over eight waves (ages 4–15 years), coded by Australian Dietary Guidelines and summed into a continuous diet score (0–14). Outcomes were adolescent (Wave 8, age 15 years) blood pressure, resting heart rate, pulse wave velocity, carotid intima-media thickness, retinal arteriole-to-venule ratio. Latent class analysis identified ‘typical’ dietary trajectories from childhood to adolescence. Adjusted linear regression models assessed relationships between trajectories and cardiovascular outcomes, adjusted for a priori potential confounders.

Community sample, Melbourne, Australia.

Children (n 188) followed from age 4 to 15 years.

Four dietary trajectories were identified: unhealthy (8 %); moderately unhealthy (25 %); moderately healthy (46 %); healthy (21 %). There was little evidence that vascular phenotypes associated with the trajectories. However, resting heart rate (beats/min) increased (β; 95 % CI) across the healthy (reference), moderately healthy (4·1; −0·6, 8·9; P=0·08), moderately unhealthy (4·5; −0·7, 9·7; P=0·09) and unhealthy (10·5; 2·9, 18·0; P=0·01) trajectories.

Decade-long dietary trajectories did not appear to influence macro- or microvascular structure or stiffness by mid-adolescence, but were associated with resting heart rate, suggesting an early-life window for prevention. Larger studies are needed to confirm these findings, the threshold of diet quality associated with these physiological changes and whether functional changes in heart rate are followed by phenotypic change.