Above average increases in body fat from 9 to 15 years of age had a negative impact on academic performance, independent of physical activity.

AIM: The associations between body fat levels and physical activity with academic performance are inconclusive and were explored using longitudinal data. METHODS: We enrolled 134/242 adolescents aged 15, who were studied at the age of nine and agreed to be followed up from April to May 2015 for the Health behaviours of Icelandic youth study. Accelerometers measured physical activity, body mass indexes (BMI) were calculated and dual-energy X-ray absorptiometry scans assessed the participants' body composition at nine and 15. Their language and maths skills were compared to a growth model that estimated the academic performances of children born in 1999. RESULTS: Higher than normal body fat levels between the ages of nine and 15 were negatively associated with maths performance, but the same association was not found for Icelandic language studies. These were Pearson's r = -0.24 (p = 0.01) for BMI and Pearson's r = -0.34 (p = 0.01) for the percentage of body fat. No associations were found with changes in physical activity. CONCLUSION: Children who put on more body fat than normal between the ages of nine and 15 had an increased risk of adverse academic performance that was independent of changes in physical activity.

Organized leisure-time sport participation and academic achievement in preadolescents.

AIMS: The aims of this study were to study the correlation between lifestyle-related factors, such as organized leisure-time sport participation (OLSP), cardiorespiratory fitness, and adiposity, and academic achievement among preadolescents. METHODS: A cross-sectional study involving 248 nine-year-old school children was carried out. OLSP was self-reported with parental assistance, categorized as ≤ 1× a week, 2-3× a week, and ≥ 4× times a week or more. Academic achievement was estimated with results from standardized test scores in Icelandic and math. Cardiorespiratory fitness was estimated using a maximal cycle ergometer test. The sum of four skinfolds was used to estimate adiposity. RESULTS: Tests of between-subjects effect indicated that OLSP significantly correlated with achievement in math only (F(2,235) = 3.81, p = 0.024). Further analysis showed that the two less active groups had significantly lower scores in math compared to the most active group with OLSP ≥ 4× times a week or more (2-3× times a week, unstandardized coefficient (b) = -4.08, 95% confidence interval (CI) [-7.09, -1.07]; ≤ 1× a week, b = -3.84, 95% CI [-7.59, -0.08]), independent of sex, age, maturity level (age to/from peak height velocity), family structure, and parental education. Neither cardiorespiratory fitness nor adiposity significantly correlated with academic achievements. CONCLUSIONS: The study's result indicates that frequent (four times per week or more often) sport participation is not harmful but may be beneficial to learning. However, further intervention-based study of this topic is needed to determine if this relationship is causal.

The association of cardiorespiratory fitness to health independent of adiposity depends upon its expression.

BACKGROUND: The strong relation between cardiorespiratory fitness (CRF) and adiposity renders their independent associations to metabolic risk factors difficult to ascertain. AIM: To determine the associations of CRF and CRF relative to fat-free mass (CRFFFM) to total cholesterol, high-density lipoprotein, low-density lipoprotein, triglycerides, glucose, insulin and homeostasis model assessment (HOMA) and distinguish these relations from the association to adiposity. SUBJECTS AND METHODS: Anthropometrics, body fat percentage (%Fat) and fat-free mass (from dual energy X-ray absorptiometry) were measured in 127 (66 females) 17 and 23 year-olds. CRF from a maximal workload on a graded bicycle test and fasting blood samples were obtained. RESULTS: CRF was significantly related to total cholesterol, triglycerides, insulin and HOMA (r = -0.24 to -0.49, p < 0.03), as were all adiposity measures (r = 0.21-0.53, p < 0.05). Correcting CRF for %Fat rendered the relation to metabolic risk factors non-significant (p = 0.09-0.21); however, CRFFFM was significantly related to the metabolic risk factors (r = -0.25 to -0.32, p < 0.02). CONCLUSIONS: CRFFFM, where adiposity has been removed, is associated with metabolic risk factors, whereas CRF, which is related to adiposity, is not after adjustment for fatness. Previously, independent effects of CRF on health may have been underestimated by using an expression of CRF strongly related to the adiposity measures.