Obesity in children is partly due to unhealthy lifestyle behaviours, e.g., sedentary activity and poor dietary choices. This trend has been seen globally. To determine the extent of these behaviours in a Portuguese population of children, 686 children 9.5 to 10.5 years of age were studied. Our aims were to: (1) describe profiles of children’s lifestyle behaviours; (2) identify behaviour pattern classes; and (3) estimate combined effects of individual/ socio-demographic characteristics in predicting class membership. Physical activity and sleep time were estimated by 24-h accelerometry. Nutritional habits, screen time and socio-demographics were obtained. Latent Class Analysis was used to determine unhealthy lifestyle behaviours. Logistic regression analysis predicted class membership. About 78% of children had three or more unhealthy lifestyle behaviours, while 0.2% presented no risk. Two classes were identified: Class 1-Sedentary, poorer diet quality; and Class 2-Insufficiently active, better diet quality, 35% and 65% of the population, respectively. More mature children (Odds Ratio (OR) = 6.75; 95%CI = 4.74–10.41), and boys (OR = 3.06; 95% CI = 1.98–4.72) were more likely to be overweight/obese. However, those belonging to Class 2 were less likely to be overweight/obese (OR = 0.60; 95% CI = 0.43–0.84). Maternal education level and household income did not significantly predict weight status (p ≥ 0.05).

The aim of this study was to identify child and school-level characteristics that explained inter-individual differences in gross motor coordination (GMC). Participants (n = 390), recruited from 18 Portuguese primary schools, were aged 6 to 10 years of age. Birth weight, body fat (BF), physical activity (PA), physical fitness (PF) and GMC were assessed. School size, setting, infrastructure and physical education classes were considered as school context markers. A multilevel modeling approach was used to identify hierarchical effects (child and school levels). It was found that children-level variables (sex, PF, and BF) significantly explained 63% of the 90% variance fraction at the individual level; boys outperformed girls (p < 0.05), individuals with higher BF were less coordinated (p < 0.05), and those with higher PF were more coordinated (p < 0.05). School-variables (e.g. school size and playing surface) explained 84% of the 10% variation fraction. These findings confirm the roles of sex, PFS and BF. Interestingly they also suggest that the school environment plays a minor but significant role in GMC development. However, it is important to stress that the school context and conditions can also play an important role in a child’s motor development, providing adequate and enriching motor opportunities.

There are widespread differences in overweight/obesity prevalence in children, and understanding the reasons for this is very important. The present study aims: (I) to conduct a meta-analysis on overweight/obesity prevalence in Portuguese children; (II) to identify differences in biological and behavioural characteristics between normal-weight and overweight/obese children; and (III) to investigate the importance of individual- and school-level correlates of variation in children’s BMI using multilevel modelling. A search was done for all published papers including Portuguese children during the last decade; further, 686 Portuguese children (9–11 years old) were sampled and their BMI, family income, maturity offset, nutritional habits, physical activity, sedentariness, sleep time, and school environment information were collected. Results showed a stabilization of overweight/obesity during the last decade, 30.6% (95%CI: 0.287–0.34) for boys, 28.4% (95%CI: 0.23–0.35) for girls, and 30.3% (95%CI: 0.27–0.34) for boys and girls together. Differences between weight groups were only found in individual-level biological traits. The multilevel analysis did not identify significant contributions of school-level variables to children’s BMI variation. In conclusion, no increase was found in the prevalence of overweight/obesity among Portuguese children since 2000. Normal-weight and overweight/obese children only differ in individual-level characteristics, and school context variables were not related to variation in BMI.

The objective of this study is to present a model to estimate sex-specific genetic effects on physical activity (PA) levels and sedentary behaviour (SB) using three generation families. The sample consisted of 100 families covering three generations from Portugal. PA and SB were assessed via the International Physical Activity Questionnaire short form (IPAQ-SF). Sex-specific effects were assessed by genotype-by-sex interaction (GSI) models and sex-specific heritabilities. GSI effects and heterogeneity were tested in the residual environmental variance. SPSS 17 and SOLAR v. 4.1 were used in all computations. The genetic component for PA and SB domains varied from low to moderate (11 % to 46 %), when analyzing both genders combined. We found GSI effects for vigorous PA (p = 0.02) and time spent watching television (WT) (p < 0.001) that showed significantly higher additive genetic variance estimates in males. The heterogeneity in the residual environmental variance was significant for moderate PA (p = 0.02), vigorous PA (p = 0.006) and total PA (p = 0.001). Sex-specific heritability estimates were significantly higher in males only for WT, with a male-to-female difference in heritability of 42.5 (95 % confidence interval: 6.4, 70.4). Low to moderate genetic effects on PA and SB traits were found. Results from the GSI model show that there are sex-specific effects in two phenotypes, VPA and WT with a stronger genetic influence in males.

This study aimed to jointly analyse moderate-to-vigorous physical activity (MVPA) and sedentariness, and their correlates, in children within their school contexts, using a multivariate multilevel approach. The sample comprises 499 Portuguese children (284 girls) from 23 schools. MVPA and sedentary time were estimated by accelerometer. A set of predictor variables from both child and school levels was tested. Overall, schools explained a small amount of the total variance in both MVPA (5.6%) and sedentariness (3.2%), and a correlation coefficient of −0.45 (p < 0.05) was found between MVPA and sedentariness at the child level. Number of siblings and socioeconomic status (SES) were significantly associated with both sedentariness (SES: β = 2.372 ± 1.183; siblings: β = −8.127 ± 2.759) and MPVA (SES: β = −1.535 ± 0.421; siblings: β = 2.822 ± 0.977), but with opposite signs. Body Mass Index (BMI) (β = −4.804 ± 1.898) and sex (male) (β = 21.561 ± 3.496) were only associated with MVPA. None of the school correlates were statistically significant in their joint effects to simultaneously explain sedentariness and MVPA. These results suggest that although MVPA and sedentariness may be different constructs, they are correlated and this should be taken into account when designing strategies to reduce children’s sedentariness and increase their MVPA. In addition, the small effect of the school context on this relationship highlights the important roles of child and family characteristics.