A multilevel analysis of health-related physical fitness. The Portuguese sibling study on growth, fitness, lifestyle and health

Sibling Resemblances in Physical Fitness in Three Distinct Regions in Peru: The Peruvian Sibling Study on Growth and Health

We estimated sibling resemblance in health-related physical fitness (PF) and examined how individual characteristics and shared natural environment accounted for sibling similarities. The sample comprised 656 sibling pairs and 102 triplets (6-15 years of age), from three geographical areas of Peru. PF components included morphological (waist circumference, sum of skinfolds), muscular (handgrip strength, standing long jump), and motor (shuttle-run). Body mass index (BMI) and somatic maturation were also assessed. In general, sibling intraclass correlations differed significantly across sib-ship types for waist circumference and handgrip strength but were the same for sum of skinfolds, standing long jump, and shuttle-run. Further, in general, both individual characteristics and geographical area of residence significantly influenced the magnitude of sibling resemblance as well as the mean levels of PF. In conclusion, individual characteristics and shared natural environment jointly influenced the expression of PF in Peruvian siblings, revealing the importance of these features when designing individualized programs promoting fitness.

Change and Stability in Sibling Physical Fitness: The Portuguese Sibling Study

PURPOSE

This study aims to 1) describe mean changes in muscular and motor fitness components in sibships over 2 yr, 2) analyze individual tracking of fitness within sibships, 3) investigate sibling resemblance in fitness over time, and 4) examine the joint influence of biological, behavioral, and familial characteristics on fitness.

METHODS

The sample comprises 166 Portuguese biological sibling pairs (brother-brother, sister-sister, brother-sister) age 9-17 yr assessed at baseline and 2 yr later. Physical fitness components were measured with standardized tests. Percentage body fat and biological maturation were assessed, and physical activity, diet, screen time, and familial characteristics were obtained by questionnaires. Multilevel models were used to analyze the clustered longitudinal data.

RESULTS

Crude results showed that, on average, all sib-types increased their muscular and motor fitness components from baseline to follow-up (except sister-sister pairs in standing long jump and shuttle run). When adjusted for covariates, the mean changes were no longer significant. Individual tracking was moderate to high for the muscular component but low to moderate for the motor component. Consistency in sibling resemblance was higher in sister-sister pairs than in brother-brother and brother-sister pairs. More mature sibs were fitter in both components, whereas siblings with higher body fat percentage were less fit. Screen time, physical activity, and parental occupation were not associated with fitness components.

CONCLUSIONS

Biological characteristics were more strongly associated with fitness components than individual behaviors and familial characteristics. Furthermore, the muscular component tracked better than the motor component. Sister-sister pairs had greater resemblance in fitness over time compared with brother-brother or sister-brother pairs.

Familial Resemblance in Body Shape and Composition, Metabolic Syndrome, Physical Activity and Physical Fitness: A Summary of Research in Portuguese Families and Siblings

We report a summary of Portuguese families and siblings research under the umbrella of the Portuguese Healthy Family Project. Families lived in mainland Portugal, as well as in the Azores and Madeira islands. All samples comprise children and adolescents (9-20 years) and their parents (27-57 years). Recruitment procedures and phenotypes were detailed. Familial resemblance in body shape and composition, metabolic syndrome, physical fitness, physical activity and sedentary behaviors are presented, as well as future research avenues.

Can waist circumference provide a new "third" dimension to BMI when predicting percentage body fat in children? Insights using allometric modelling

INTRODUCTION

Body mass index (BMI) is often criticized for not being able to distinguish between lean and fat tissue. Waist circumference (WC), adjusted for stature, is proposed as an alternative weight status index, as it is more sensitive to changes in central adiposity.

PURPOSE

The purpose of the study is to combine the three dimensions of height, mass, and WC to provide a simple, meaningful, and more accurate index associated with percentage body fat (BF%).

METHODS

We employed a four independent sample design. Sample 1 consisted of 551 children (320 boys) (mean ± SD of age = 7.2 ± 2.0 years), recruited from London, UK. Samples 2, 3, and 4 consisted of 5387 children (2649 boys) aged 7 to 17 years recruited from schools in Portugal. Allometric modelling was used to identify the most effective anthropometric index associated with BF%. The data from samples 2, 3, and 4 were used to confirm and cross-validate the model derived in sample 1.

RESULTS

The allometric models from all four samples identified a positive mass exponent and a negative height exponent that was approximately twice that of the mass exponent and a waist circumference exponent that was approximately half the mass exponent. Consequently, the body shape index most strongly associated with BF% was <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>BMI</mml:mi> <mml:msqrt><mml:mi>WC</mml:mi></mml:msqrt> </mml:math> . The <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msqrt><mml:mi>WC</mml:mi></mml:msqrt> </mml:math> component of the new index can simply be interpreted as a WC "weighting" of the traditional BMI.

CONCLUSIONS

Compared with using BMI and WC in isolation, <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>BMI</mml:mi> <mml:msqrt><mml:mi>WC</mml:mi></mml:msqrt> <mml:mspace/></mml:math> could provide a more effective and equally noninvasive proxy for BF% in children that can be used in public and community health settings.

Sibling Similarity in Metabolic Syndrome: The Portuguese Sibling Study on Growth, Fitness, Lifestyle and Health

This study aims to estimate sibling resemblance in metabolic syndrome (MS) markers, and to investigate the associations of biological and behavioral characteristics with MS. The sample comprises 679 biological siblings (363 females; 316 males) aged 9-20 years. MS markers included waist circumference (WC), high-density lipoprotein cholesterol (HDL-C), triglycerides (TRI), fasting glucose (GLU) and systolic blood pressure (SBP). Body mass index (BMI), biological maturation, muscular, and cardiorespiratory fitness were also assessed. Behavioral characteristics, including dietary intake and physical activity, were self-reported by questionnaire. Multilevel models were used, and sibling resemblance was estimated using the intraclass correlation (ρ). In general, same-sex siblings showed higher resemblance in MS markers than opposite-sex siblings. However, variability in sibling resemblance in MS markers was evident with the inclusion of covariates. Biological characteristics including age, BMI and maturity offset influenced all MS markers except for TRI. Importantly, behavioral characteristics diversely influenced MS markers: fruit and vegetables only influenced SBP, whereas physical activity affected HDL-C. Additionally, muscular fitness impacted significantly on MS Z-score, WC, SBP and GLU, whilst cardiorespiratory fitness only affected WC. In conclusion, biological and behavioral characteristics influenced the expression of MS markers. These results confirmed the importance of considering individual characteristics when designing individualized programs for diminishing the adverse effects of specific MS markers.

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.

Change and Stability in Sibling Resemblance in Obesity Markers: The Portuguese Sibling Study on Growth, Fitness, Lifestyle, and Health

BACKGROUND/OBJECTIVES

Obesity markers evolve over time and these changes are shared within the family orbit and governed by individual and environmental characteristics. Available reports often lack an integrated approach, in contrast to a multilevel framework that considers their concurrent influence. Hence, this study aims to (1) describe mean changes in obesity markers (body fat (%BF), body mass index (BMI), and waist circumference (WC)) across sib-ships; (2) analyze tracking of individuals within their sib-ship in these markers during 2 years of follow-up; (3) probe consistency in sibling resemblance in these markers; and (4) analyze the joint influence of individual and familial characteristics in these markers.

SUBJECTS/METHODS

The sample comprises 168 biological Portuguese siblings (brother-brother (BB), sister-sister (SS), and brother-sister (BS)) aged 9-17 years. %BF, BMI, and WC were measured using standardized protocols, and biological maturation was assessed. Physical activity, diet, screen time, and familial characteristics were obtained by questionnaires. Multilevel models were used to analyze the clustered longitudinal data. Sibling resemblance was estimated with the intraclass correlation.

RESULTS

On average, all sib types increased in BMI and WC over 2 years of follow-up, and SS pairs increased in %BF. Individuals within sib-ships track high in all obesity markers across time. Consistency in siblings' resemblance was also noted, except for BB pairs in %BF which decreased at follow-up. More maturing siblings tend to have higher values in all markers. Greater screen time was associated with higher %BF, whereas those consuming more sugary drinks had lower %BF and BMI values. Siblings whose mothers had less qualified occupations tended to have lower BMI values.

CONCLUSIONS

Longitudinal individual tracking and sibling resemblance for obesity markers were found. Yet, different trajectories were also identified depending on the marker and sib type. Individual and familial characteristics exert different influences on each obesity marker.

Profile Resemblance in Health-Related Markers: The Portuguese Sibling Study on Growth, Fitness, Lifestyle, and Health

The co-occurrence of health-related markers and their associations with individual, family, and environmental characteristics have not yet been widely explored in siblings. We aimed to identify multivariate profiles of health-related markers, analyze their associations with biological, sociodemographic, and built environment characteristics, and estimate sibling resemblance in these profiles. The sample includes 736 biological siblings aged 9–20 years. Body fat was measured with a portable bioelectrical impedance scale; biological maturation was assessed with the maturity offset; handgrip strength, standing long jump, one-mile run, and shuttle run were used to mark physical fitness. Health behaviors, sociodemographic, and built environmental characteristics were recorded by questionnaire. Latent profile analysis and multilevel logistic regression models were used; sibling resemblance was estimated with the intraclass correlation (ρ). Two multivariate profiles emerged: “P1 = fit, lower fat and poorer diet” (86.7%) and “P2 = higher fat and lower fit, but better diet” (13.3%). Siblings whose fathers were less qualified in their occupation were more likely to belong to P2 (OR = 1.24, p = 0.04); those whose fathers with Grade 12 and university level education were more likely to fit in P2 compared to peers living with fathers having an educational level below Grade 12 (OR = 3.18, p = 0.03, and OR = 6.40, p = 0.02, Grade 12 and university level, respectively). A moderate sibling profile resemblance was found (0.46 ≤ ρ ≤ 0.55). In conclusion, youth health-related markers present substantial differences linked with their body composition, physical fitness and unhealthy diet. Furthermore, only father socio-demographic characteristics were associated with profile membership. Sibling´s profile resemblance mirrors the effects of genetics and shared characteristics.

How Consistent are Genetic Factors in Explaining Leisure-Time Physical Activity and Sport Participation? The Portuguese Healthy Families Study

This study investigates how consistent genetic factors are, as measured by heritability estimates (h2), in the leisure-time physical activity index (LTPAI) and sport participation index (SPI) from early (10-14 yrs) to late adolescence (15-19 yrs). The sample comprises 12,385 subjects from 3,378 Portuguese nuclear families. Height and weight were measured and body mass index (BMI) was calculated, and the LTPAI and SPI were estimated by questionnaire. Socioeconomic status (SES) was assessed by parental occupation. Analyses were done using S.A.G.E. software. Our results showed that h2 estimates for the LTPAI and SPI in the two age groups (10-14 yrs and 15-19 yrs) were stable: for the LTPAI, h2 = 0.297 and 0.322, respectively; and for the SPI, h2 = 0.413 and 0.428, respectively. Sibling correlations and environmental correlations are higher in the younger age group for both the LTPAI and the SPI. Spousal correlations are higher in the younger age group for the LTPAI and lower for the SPI than the older group. Parent-offspring correlations are similar in both age groups for the LTPAI and SPI. In conclusion, the influence of genetic factors on physical activity and sport participation remains stable across age in adolescence. However, variation in sibling correlations - in particular, environmental correlations - was observed. These findings suggest that shared/non-shared environmental factors express different degrees of importance across age. Future intervention programs aiming to promote change in behaviors need to consider these results to bring about positive changes in physical activity and sport participation behaviors within the family setting.