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This article is divided into two parts: part I consists of the position stand of The Canadian Association of Applied Sport Sciences on the involvement of children in competitive sports, and part II presents scientific background and rationale pertinent to the position statements. Each part is divided into major categories reflecting the multi-disciplinary concerns of the participation of pre- and post-pubescent children in sport situations at all levels. Psychological considerations focus on the child learning a sense of competence and control through sports participation. Success in a sport should not be based solely on winning, but on one's own performance and attained goals. Sport involvement can provide one important avenue for a child's social development. Non-aggressive behaviour and a constructive problem-solving approach should be encouraged. Any form of discrimination towards sports participation or competition should be discouraged. From the physiological and medical point of view, it should be recognized that each child is different in his/her response and tolerance to exercise due to a great range of variability in growth rates, anthropometric indices, gender and state of health, even in children of a similar chronological age. Younger prepubertal children should be encouraged to participate in a wide variety of motor skills, whereas older post-pubertal children can become more specialized in their training and sport participation. A child's performance and adaptation to training should not be directly compared to an adult's as significant differences exist, especially during the years of accelerated growth. Environmental exercise tolerance is also more limited to children than adults. In younger children repetitive heavy loading of the musculoskeletal system should be approached with caution. With proper equipment, design and usage, and rule modifications, serious injuries can be avoided. Medical disabilities should be evaluated on an individual basis and should not necessarily preclude a child's participation. Teachers, parents and coaches should have a thorough understanding of the implications of children involved in sports and adhere to the recommendations reviewed in this statement.

Inflammation is an important factor linking abdominal obesity with insulin resistance and related cardiometabolic risk. A genome‐wide association study of adiposity‐related traits performed in the Quebec Family Study (QFS) revealed that a single‐nucleotide polymorphism (SNP) in the LRRFIP1 gene (rs11680012) was associated with abdominal adiposity ( P = 4.6 × 10 –6 ). Objective: The objective of this study was to assess the relationship between polymorphisms in LRRFIP1 gene and adiposity (BMI, fat mass (FM), waist circumference (WC), and computed tomography‐derived areas of total, subcutaneous and visceral abdominal adipose tissue) and markers of inflammation (C‐reactive protein (CRP) and interleukin‐6 (IL‐6)). Design and Methods: Using Sequenom, 16 tag SNPs in the LRRFIP1 gene, capturing 78% of the genetic variation, were genotyped in 926 participants of the QFS. Results: Eight SNPs (rs7575941, rs3769053, rs11689421, rs3820808, rs11680012, rs3806505, rs6739130, and rs11686141) showed evidence of association with at least two adiposity phenotypes and plasma levels of one marker of inflammation. The strongest evidence of association was observed with rs11680012, which explained 1.8–3.4% of the variance in areas of abdominal adiposity and 2.0% of the variation in CRP levels. Carriers of the rare allele of rs11680012 had ∼30% more abdominal adiposity ( P values between 2.7 × 10 –4 and 3.8 × 10 –6 ) and 75% higher CRP levels ( P = 1.6 × 10 –4 ) than the common allele in age and sex adjusted data. Rs11680012 is a G/C SNP converting an arginine into a threonine and this amino acid substitution may potentially alter exonic splicing. Conclusion: This gene may therefore represent a potential interesting target to investigate in further functional studies on adiposity and inflammation.

Background Recent studies showed that eating behaviors such as disinhibition, emotional and external eating, and snacking mediate genetic susceptibility to obesity. It remains unknown if diet quality and intake of specific food groups also mediate the genetic susceptibility to obesity. Objective This study aimed to assess if diet quality and intakes of specific food groups mediate the association between a polygenic risk score (PRS) for BMI and BMI and waist circumference (WC). We hypothesized that poor diet quality, high intakes of energy-dense food groups, and low intakes of nutrient-dense food groups mediate the genetic susceptibility to obesity. Methods This cross-sectional study included 750 participants (56.3% women, aged 41.5 ± 14.9 y, BMI 27.8 ± 7.5 kg/m2) from the Quebec Family Study. A PRSBMI based on >500,000 genetic variants was calculated using LDpred2. Dietary intakes were assessed with a 3-d food record from which a diet quality score (i.e. Nutrient Rich Food Index 6.3) and food groups were derived. Mediation analyses were conducted using a regression-based and bootstrapping approach. Results The PRSBMI explained 25.7% and 19.8% of the variance in BMI and WC, respectively. The association between PRSBMI and BMI was partly mediated by poor diet quality (β = 0.33 ± 0.12; 95% CI: 0.13, 0.60), high intakes of fat and high-fat foods (β = 0.46 ± 0.16; 95% CI: 0.19, 0.79) and sugar-sweetened beverages (β = 0.25 ± 0.14; 95% CI: 0.05, 0.60), and low intakes of vegetables (β = 0.15 ± 0.08; 95% CI: 0.03, 0.32), fruits (β = 0.37 ± 0.12; 95% CI: 0.17, 0.64), and dairy products (β = 0.17 ± 0.09; 95% CI: 0.02, 0.37). The same trends were observed for WC. Conclusions The genetic susceptibility to obesity was partly mediated by poor diet quality and intakes of specific food groups. These results suggest that improvement in diet quality may reduce obesity risk among individuals with high genetic susceptibility and emphasize the need to intervene on diet quality among these individuals.

This study aimed at characterizing the interactions between a complex peptide mixture and the G-10 membrane (Osmonics, Minnetonka, MN) as influenced by pH. It was previously shown that the composition of the peptide layer interacting with the G-10 membrane and causing fouling was pH-dependent. An adsorption–desorption procedure was used to evaluate the effect of pH (5 and 9) and added CaCl2 (0.01M) on the profile of peptides adsorbed onto the G-10 membrane. Modifications of the surface properties of the G-10 membrane upon adsorption of tryptic β-LG peptides were also estimated using contact angle measurements. These methods demonstrated that the nature of the tryptic peptides contained in a β-LG hydrolysate adsorbing onto the G-10 membrane was influenced by the pH and the presence of Ca2+ ions. The selective influence of the pH was attributed to changes in the ionization state of the membrane. At pH 9, mostly basic (positive) peptides were able to interact with the membrane while at pH 5 no direct correlation with the pI of the peptides was obtained. Hydrophobic interactions were shown to be involved in the adsorption as evidenced with sequence β-LG 15–20. This peptide is thought to play a key role in the build-up of the fouling layer, determining the resulting sieving properties of the G-10 membrane during NF.

Regional fat distribution is related to higher risks of cardiovascular morbidity and mortality, independent of general obesity. In particular, a centralized pattern of fat deposition, characterized by greater abdominal stores relative to extremity stores, is associated with a higher propensity to metabolic complications. Motivated by these considerations, we have initiated a systematic investigation of several measures of regional fat distribution aimed at the identification of possible major gene effects. Two measures approximate the size of subcutaneous fat stores: the sum of six skinfold thicknesses (SF6 = abdominal + suprailiac + subscapular + calf + triceps + biceps), and the sum of three trunk skinfold thicknesses (TSF3 = abdominal + suprailiac + subscapular). Both of these phenotypes are highly correlated with total fat mass, 0.83 and 0.78 for SF6 and TSF3, respectively. The trunk to extremity ratio [TER = TSF3/ (calf + triceps + biceps)] is perhaps the most important of these phenotypes insofar as it is an index of centralized obesity; it is modestly correlated with fat mass (r = 0.18). Each of these phenotypes was adjusted for total fat mass by regression prior to analysis so that we could examine genetic effects on these measures of regional fat distribution without the confounding influence of the determinants of fat mass itself. Segregation analysis of SF6 and TSF3 controlled for total fat mass suggests the presence of a major effect underlying the observed phenotypic distribution; however, tests on the transmission probabilities did not substantiate the segregation of a Mendelian gene.(ABSTRACT TRUNCATED AT 250 WORDS)

Several epidemiological studies have reported that the regional distribution of body fat is a significant and independent risk factor for cardiovascular disease (CVD) and related mortality. Although these associations are well established, the causal mechanisms are not fully understood. Numerous studies have, however, shown that specific topographic features of adipose tissue are associated with metabolic complications that are considered as risk factors for CVD such as insulin resistance, hyperinsulinemia, glucose intolerance and type II diabetes mellitus, hypertension, and changes in the concentration of plasma lipids and lipoproteins. The present article summarizes the evidence on the metabolic correlates of body fat distribution. Potential mechanisms for the association between body fat distribution, metabolic complications, and CVD are reviewed, with an emphasis on plasma lipoprotein levels and plasma lipid transport. From the evidence available, it seems likely that subjects with visceral obesity represent the subgroup of obese individuals with the highest risk for CVD. Although body fat distribution is now considered as a more significant risk factor for CVD and related death rate than obesity per se, further research is clearly needed to identify the determinants of body fat distribution and the causal mechanisms involved in the metabolic alterations. It appears certain, however, that an altered plasma lipid transport is a significant component of the relation between body fat distribution and CVD.

Thérlault, G.; Després, J.-P.; Maheux, J.; Bessette, H.; Tremblay, A.; Bouchard, C. Author Information

PURPOSE: This study determined the reproducibility of resting systolic and diastolic blood pressure, mean arterial pressure, and heart rate (the average of three measures/day). METHODS: The data were obtained on two separate days prior to an exercise training intervention in a sample of 822 subjects participating in the HERITAGE Family Study. The same protocol was conducted across three days in an intracenter quality control substudy, which included an additional 60 subjects. RESULTS: Reproducibility estimates included technical error, coefficient of variation within subjects, and intraclass correlation with results expressed by sex, race, age, cuff size, BMI, and %fat. Since the data were collected across four Clinical Centers, the reproducibility estimates were also computed separately for each Center. The systolic, diastolic, and mean arterial blood pressures were highly reproducible with technical errors less than 5.1 mmHg, coefficients of variation of less than 7.0% and intraclass correlations > 0.75. The heart rates were slightly less reproducible. These results were fairly consistent across subject populations and across all four Clinical Centers. CONCLUSION: It is concluded that within subject day-to-day variations are small compared to between subject variance for resting systolic, diastolic, and mean arterial blood pressure and heart rate at each of the Clinical Centers for all of the HERITAGE Family Study data. This makes it appropriate to pool the data and analyze it for changes subsequent to endurance exercise training and to determine the possible genetic basis for these changes.

The etiology of familial resemblance for systolic (SBP) and diastolic (DBP) blood pressure, both within a single time point as well as across time points, was assessed to determine how familial etiologies underlying a trait may change across time. SBP and DBP measurements were taken roughly 12 years apart in family members participating in the longitudinal Québec Family Study. A longitudinal (bivariate) familial correlation model yields 3 types of correlations: intraindividual cross-time (e.g., father's BP at time 1 with his own BP at time 2); interindividual within-time (e.g., father time 1 with child time 1); and interindividual cross-time (e.g., father time 1 with child time 2). In addition, the change in BP across time (i.e., time 1-time 2) is examined using a univariate family correlation model. This combined method is useful in assessing the degree to which the same familial factors are operating across time (interindividual cross-time correlations), as well as the degree to which different heritable components are involved across time (change score). Maximal heritabilities for SBP were about 70% at each time point, while for DBP the heritability was larger at time 1 (87%) than time 2 (39%). Both the change scores (48% for SBP and 54% for DBP) and the cross-time comparisons (58% to 72% for SBP and 63% to 65% for DBP) evidenced significant familial resemblance. These results illustrate how simple methodologies can be used to specify how familial etiologies underlying a trait may change across time. For BP, the model includes unique familial factors that are specific to each time measurement, and an additional familial factor which is common to both time points. The factors leading to differences in longitudinal familial resemblance for BP (i.e., the unique factors) may be primarily genetic in origin, while those leading to stability across time may include both genetic and familial environmental effects. Sex and/or age interactions with the genotypes are also suggested.

The purpose of this study was to identify regions of the human genome linked to submaximal exercise heart rates in the sedentary state and in response to a standardized 20-wk endurance training program in blacks and whites of the HERITAGE Family Study. A total of 701 polymorphic markers covering the 22 autosomes were used in the genome-wide linkage scan, with 328 sibling pairs from 99 white nuclear families and 102 pairs from 115 black family units. Steady-state heart rates were measured at the relative intensity of 60% maximal oxygen uptake (HR60) and at the absolute intensity of 50 W (HR50). Baseline phenotypes were adjusted for age, sex, and baseline body mass index (BMI) and training responses (posttraining minus baseline, Delta) were adjusted for age, sex, baseline BMI, and baseline value of the phenotype. Two analytic strategies were used, a multipoint variance components and a regression-based multipoint linkage analysis. In whites, promising linkages (LOD > 1.75) were identified on 18q21-q22 for baseline HR50 (LOD = 2.64; P = 0.0002) and DeltaHR60 (LOD = 2.10; P = 0.0009) and on chromosome 2q33.3 for DeltaHR50 (LOD = 2.13; P = 0.0009). In blacks, evidence of promising linkage for baseline HR50 was detected with several markers within the chromosomal region 10q24-q25.3 (peak LOD = 2.43, P = 0.0004 with D10S597). The most promising regions for fine mapping in the HERITAGE Family Study were found on 2q33 for HR50 training response in whites, on 10q25-26 for baseline HR60 in blacks, and on 18q21-22 for both baseline HR50 and DeltaHR60 in whites.

Introduction: Lipoproteins are among the strongest predictors of CVD and are altered through regular exercise. However, the molecular changes underlying the potential benefits of exercise on plasma lipoproteins are unclear. Methods: Proteins (n=4979) were quantified from the plasma of 647 Black and White adults (56% women, mean age = 34.9 yrs) before and after 20-weeks of endurance exercise training using SomaScan. All subjects had complete data for 7 lipoprotein traits that improved with training: HDL-C, TG, large TG rich lipoprotein particles (LTRLP), small LDL particles (SLDLP), large HDL particles (LHDLP), TRLP size, and LDLP size. Fully adjusted linear mixed models were used to test the association of 1) baseline proteins with baseline lipoproteins and 2) delta proteins with delta lipoproteins (delta = post training - baseline value). Significance was determined as FDR<0.05. Results: We identified numerous proteins associated with baseline levels of at least one of the seven lipoprotein traits (range: 48-1099) and whose changes in response to regular exercise were associated with concomitant changes in lipoproteins (range: 4-95) ( Table 1 ). Substantial overlap was found between proteins associated with lipoproteins across timepoints, with 16 proteins associated with 4 or more lipoprotein traits at both timepoints. Plasma abundance of 12/16 proteins significantly changed with training (FDR <0.05). Additionally, for these proteins plasma abundance changed in concordance with the beneficial direction of the associated lipoprotein trait (e.g., proteins associated with atheroprotective lipoprotein traits increased with training and proteins associated with atherogenic traits decreased). Conclusions: Beneficial alterations to plasma lipoproteins with regular exercise are reflected in changes to the plasma proteome. Proteins identified here may represent novel markers of the benefits of regular exercise and of systemic lipoprotein metabolism.