Are there gross motor coordination spurts during mid-childhood?

OBJECTIVES: The aims of this study were (1) to identify the timing of the mid-growth spurt (MGS) in stature in children and (2) to identify gross motor coordination (GMC) spurts when aligned by the age of attainment of the MGS (aMGS). METHODS: Stature, weight, and GMC were measured in 245 Portuguese children followed annually from 6 to 10 years. GMC was assessed and to estimate children's MGS in stature as well as GMC spurts in each of the four tests aligned by aMGS, we used a nonsmoothed polynomial methodology. RESULTS: In boys, the aMGS was attained at 7.8 years, whereas in girls it was 8.0 years. In boys, the peak MGS was 6.2 cm∙yr-1 and in girls it was 6.4 cm∙yr-1 . In boys, the peak for walking backwards (WB) occurred 18 months before aMGS (14.9-points∙yr-1 ), jumping sideways (JS) was 12 months after aMGS (13.5-points∙yr-1 ), hopping on one leg (HO) was 18 months before aMGS (11.7-points∙yr-1 ), and shifting platform (SP) was 12 months before aMGS (6.8-points∙yr-1 ). In girls, WB spurts occurred 12 months after aMGS (13.3-points∙yr-1 ), JS was 12 months before aMGS (10.5-points∙yr-1 ), HO was coincident with aMGS (10.4-points∙yr-1 ), and SP was 18 as well as 12 months before aMGS (7.2-points∙yr-1 ). No differences were observed in the mean peak spurts between sexes in the GMC tests. CONCLUSIONS: Boys and girls reached their MGS in stature at about the same chronological age. Spurts in GMC did not express themselves in the same biological timing relative to aMGS in stature, and there are sex differences.

Familial resemblance in gross motor coordination. The Peruvian Sibling Study on Growth and Health.

BACKGROUND: The development of gross motor coordination (GMC) is governed by biological and environmental factors whose effect sizes are still unclear. AIM: To investigate sibling resemblance in GMC, as well as biological and environmental correlates of GMC among Peruvian children. MATERIALS AND METHODS: The sample comprised 1256 biological siblings (6-15 years old), from three geographical areas of Peru. GMC was assessed using the Korperkoordinationtest für Kinder (KTK) test battery. Anthropometry, biological maturation and physical fitness (PF) were also measured. Multilevel modelling was performed using Stata 14 software. RESULTS: In general, sister-sister pairs (SS) showed the highest resemblance in GMC (ρ = 0.24) compared to brother-sister (BS) (ρ = 0.10) and brother-brother (BB) pairs (ρ = 0.07). On average, BB pairs had higher GMC than SS pairs and older siblings had higher GMC than younger siblings. Further, those with lower body mass index (BMI) and higher PF had higher GMC. There was also a significant interaction between age and PF with GMC. Siblings from the rainforest region demonstrated higher GMC than those from sea level and high-altitude siblings demonstrated lower GMC than their sea-level peers. CONCLUSION: These results demonstrate statistically significant sibling resemblance in GMC. Age, BMI, PF and geographical area were significant correlates of GMC.

A multi-level analysis of individual- and school-level correlates of physical fitness in children.

BACKGROUND: Children's physical fitness is potentially influenced by biological, behavioural and environmental factors. AIM: To investigate the importance of individual-level and school-level characteristics in explaining variation in children's physical fitness. SUBJECTS AND METHODS: The sample comprised 354 Portuguese children, aged 5-10 years. Physical fitness [(handgrip (HG) strength, standing long jump (SLJ), shuttle-run (SR), total physical fitness score (PFz)], gross motor coordination (GMC) and body mass index (BMI) were assessed. Moderate-to-vigorous physical activity (MVPA) was objectively monitored; birth weight and socio-economic status (SES) were obtained by questionnaire. School contexts were assessed via an objective audit. Multilevel models using the Bayesian approach were used. RESULTS: Age was positively associated with HG, SLJ and PFz (p < 0.05); BMI was positively associated with HG (p < 0.05) and GMC with all physical fitness components (p < 0.05); MVPA was only associated with PFz (p < 0.05); children with level A SES outperformed those with level C SES in HG (p < 0.05), but those with level B SES outperformed their level A SES peers in SR (p < 0.05). Within the school context, no equipment for physical education was negatively associated with HG (p < 0.05). CONCLUSION: In the primary school years, individual-level characteristics were more important than the school context in explaining variations in physical fitness.

Multilevel modelling of somatotype components: the Portuguese sibling study on growth, fitness, lifestyle and health.

BACKGROUND: Somatotype is a complex trait influenced by different genetic and environmental factors as well as by other covariates whose effects are still unclear. AIMS: To (1) estimate siblings' resemblance in their general somatotype; (2) identify sib-pair (brother-brother (BB), sister-sister (SS), brother-sister (BS)) similarities in individual somatotype components; (3) examine the degree to which between and within variances differ among sib-ships; and (4) investigate the effects of physical activity (PA) and family socioeconomic status (SES) on these relationships. SUBJECTS AND METHODS: The sample comprises 1058 Portuguese siblings (538 females) aged 9-20 years. Somatotype was calculated using the Health-Carter method, while PA and SES information was obtained by questionnaire. Multi-level modelling was done in SuperMix software. RESULTS: Older subjects showed the lowest values for endomorphy and mesomorphy, but the highest values for ectomorphy; and more physically active subjects showed the highest values for mesomorphy. In general, the familiality of somatotype was moderate (ρ = 0.35). Same-sex siblings had the strongest resemblance (endomorphy: ρSS > ρBB > ρBS; mesomorphy: ρBB = ρSS > ρBS; ectomorphy: ρBB > ρSS > ρBS). For the ectomorphy and mesomorphy components, BS pairs showed the highest between sib-ship variance, but the lowest within sib-ship variance; while for endomorphy BS showed the lowest between and within sib-ship variances. CONCLUSIONS: These results highlight the significant familial effects on somatotype and the complexity of the role of familial resemblance in explaining variance in somatotypes.

Variability and Stability in Daily Moderate-to-Vigorous Physical Activity among 10 Year Old Children.

Day-to-day variability and stability of children's physical activity levels across days of the week are not well understood. Our aims were to examine the day-to-day variability of moderate-to-vigorous physical activity (MVPA), to determine factors influencing the day-to-day variability of MVPA and to estimate stability of MVPA in children. The sample comprises 686 Portuguese children (10 years of age). MVPA was assessed with an accelerometer, and BMI was computed from measured height and weight. Daily changes in MVPA and their correlates (gender, BMI, and maturity) were modeled with a multilevel approach, and tracking was calculated using Foulkes &amp; Davies γ. A total of 51.3% of boys and 26.2% of girls achieved 60 min/day of MVPA on average. Daily MVPA was lower during the weekend (23.6% of boys and 13.6% of girls comply with the recommended 60 min/day of MVPA) compared to weekdays (60.8% and 35.4%, boys and girls, respectively). Normal weight children were more active than obese children and no effect was found for biological maturation. Tracking is low in both boys (γ = 0.59 ± 0.01) and girls (γ = 0.56 ± 0.01). Children's MVPA levels during a week are highly unstable. In summary, boys are more active than girls, maturation does not affect their MVPA, and obese children are less likely to meet 60 min/day of MVPA. These results highlight the importance of providing opportunities for increasing children's daily MVPA on all days of week, especially on the weekend.

Profiling physical activity, diet, screen and sleep habits in Portuguese children.

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).

Genotype by sex and genotype by age interactions with sedentary behavior: the Portuguese Healthy Family Study.

Sedentary behavior (SB) expression and its underlying causal factors have been progressively studied, as it is a major determinant of decreased health quality. In the present study we applied Genotype x Age (GxAge) and Genotype x Sex (GxSex) interaction methods to determine if the phenotypic expression of different SB traits is influenced by an interaction between genetic architecture and both age and sex. A total of 1345 subjects, comprising 249 fathers, 327 mothers, 334 sons and 325 daughters, from 339 families of The Portuguese Healthy Family Study were included in the analysis. SB traits were assessed by means of a 3-d physical activity recall, the Baecke and IPAQ questionnaires. GxAge and GxSex interactions were analyzed using SOLAR 4.0 software. Sedentary behaviour heritability estimates were not always statistically significant (p>0.05) and ranged from 3% to 27%. The GxSex and GxAge interaction models were significantly better than the single polygenic models for TV (min/day), EEsed (kcal/day), personal computer (PC) usage and physical activty (PA) tertiles. The GxAge model is also significantly better than the polygenic model for Sed (min/day). For EEsed, PA tertiles, PC and Sed, the GxAge interaction was significant because the genetic correlation between SB environments was significantly different from 1. Further, PC and Sed variance heterogeneity among distinct ages were observed. The GxSex interaction was significant for EEsed due to genetic variance heterogeneity between genders and for PC due to a genetic correlation less than 1 across both sexes. Our results suggest that SB expression may be influenced by the interactions between genotype with both sex and age. Further, different sedentary behaviors seem to have distinct genetic architectures and are differentially affected by age and sex.

Genotype by energy expenditure interaction with metabolic syndrome traits: the Portuguese healthy family study.

Moderate-to-high levels of physical activity are established as preventive factors in metabolic syndrome development. However, there is variability in the phenotypic expression of metabolic syndrome under distinct physical activity conditions. In the present study we applied a Genotype X Environment interaction method to examine the presence of GxEE interaction in the phenotypic expression of metabolic syndrome. A total of 958 subjects, from 294 families of The Portuguese Healthy Family study, were included in the analysis. Total daily energy expenditure was assessed using a 3 day physical activity diary. Six metabolic syndrome related traits, including waist circumference, systolic blood pressure, glucose, HDL cholesterol, total cholesterol and triglycerides, were measured and adjusted for age and sex. GxEE examination was performed on SOLAR 4.3.1. All metabolic syndrome indicators were significantly heritable. The GxEE interaction model fitted the data better than the polygenic model (p<0.001) for waist circumference, systolic blood pressure, glucose, total cholesterol and triglycerides. For waist circumference, glucose, total cholesterol and triglycerides, the significant GxEE interaction was due to rejection of the variance homogeneity hypothesis. For waist circumference and glucose, GxEE was also significant by the rejection of the genetic correlation hypothesis. The results showed that metabolic syndrome traits expression is significantly influenced by the interaction established between total daily energy expenditure and genotypes. Physical activity may be considered an environmental variable that promotes metabolic differences between individuals that are distinctively active.