Children and chrono-exercise: Timing of physical activity on school and weekend days depends on sex and obesity status.

Recommendations for physical activity (PA) typically focus on frequency, intensity, duration, and type, but timing (chrono-exercise) is also important. The objective of this study is to describe when children are active on school and weekend days and explore PA timing across sex and body mass index (BMI) categories. 359 children (53% male), aged 9.6 (0.9) y, were categorized as normal weight (≥-1 standard deviations (SD) and <1SD; n = 193), overweight (≥1SD and <2SD; n = 80), or obese (≥2SD; n = 86) using WHO BMIz. Moderate-to-vigorous PA (MVPA) was assessed using ActiGraph LS-7164. The results are described as Mean(SD). ANOVA evaluated MVPA across sexes and BMI categories. Normal weight boys were more active than boys with obesity on school (Δ20.33 min; p < 0.001) and weekend days (Δ15.04 min; p < 0.05). On school days, significant differences existed between 9:00 h-11:00 h and 12:00 h-14:00 h (p < 0.017), while on weekends, smaller differences existed throughout the day. Girls' MVPA was similar across BMI categories, on all days (p > 0.05). On school days, 12:00 h-13:00 h represented the most active hour for all participants (~14% total daily MVPA). Peak weekend MVPA was distributed across multiple hours. Differences in MVPA timing emerged on school-days and weekends. Timing may be important when examining the nuances of MVPA in relation to sex and bodyweight in children.

Early Lifestyle Determinants of Adiposity Trajectories from Childhood into Late Adolescence.

Objective: The aim of this study was to examine associations of childhood physical activity, sedentary behavior, and dietary intake with adiposity trajectories from childhood to adolescence. Methods: Quebec Adipose and Lifestyle Investigation in Youth (QUALITY) cohort (n = 630) data from 3 time points (8-10, 10-12, and 15-17 years) for 377 Caucasian children with parental obesity were analyzed. Height and weight, physical activity and sedentary behavior (7-day accelerometry), screen time (self-reported), and dietary intake (three 24-hour diet recalls) were measured. Group-based trajectory modeling identified longitudinal trajectories of body-mass index z-scores (zBMIs). Inverse probability of exposure-weighted multinomial logistic regressions examined associations between baseline lifestyles and zBMI trajectory groups. Results: Six trajectory groups were identified: Stable-Low-Normal-Weight (two groups, 5.7% and 33.0%, which were combined), Stable-High-Normal-Weight (24.8%), Stable-Overweight (19.8%), Stable-Obesity (8.8%), and Overweight-Decreasers (7.9%). For every additional portion of fruits and vegetables, the likelihood of being in the group of Overweight-Decreasers increased by 29% (odds ratio [OR]: 1.29, 95% confidence interval [CI]: 1.09-1.55) compared with the reference group (Stable-Low-Normal-Weight). For every additional hour of sedentary behavior, the likelihood of belonging to the group of Overweight-Decreasers increased 2-fold (OR: 1.99, 95% CI: 1.28-3.21) and Stable-Obesity increased 1.5-fold (OR: 1.56, 95% CI: 1.08-2.23), compared with the reference. Every additional 10 minutes of moderate-to-vigorous physical activity was associated with a lower likelihood of belonging to the Stable-Obesity group (OR: 0.75, 95% CI: 0.61-0.89) and to the group of Overweight-Decreasers (OR: 0.79, 95% CI: 0.64-0.95) compared with the reference. Finally, children were more likely to belong to the Stable-Obesity group with each additional hour/day of screen time (OR: 1.23, 95% CI: 1.01-1.58). Conclusions: Trajectories of zBMIs from childhood to late adolescence were stable, except for one group which decreased from overweight in childhood to normal weight in adolescence. The latter had more favorable baseline dietary intake of fruits and vegetables. ClinicalTrials.org no. NCT03356262.

The Longevity Protein Klotho: A Promising Tool to Monitor Lifestyle Improvements.

Aging is not a disease; it is a natural evolution of human physiology. Medical advances have extended our life expectancy, but chronic diseases and geriatric syndrome continue to affect the increasingly aging population. Yet modern medicine perpetuates an approach based on treatment rather than prevention and education. In order to help solve this ever-growing problem, a new discipline has emerged: lifestyle medicine. Nutrition, physical activity, stress management, restorative sleep, social connection, and avoidance of risky substances are the pillars on which lifestyle medicine is founded. The aim of this discipline is to increase healthspan and reduce the duration of morbidity by making changes to our lifestyle. In this review, we propose the use of klotho protein as a novel biomarker for lifestyle medicine in order to quantify and monitor the health status of individuals, as no integrative tool currently exists.

Trajectories of cardiorespiratory fitness from childhood to adolescence: Findings from the QUALITY cohort.

Estimate the shape and number of cardiorespiratory fitness (CRF) trajectories from childhood to adolescence; and verify whether CRF trajectory membership can be predicted by sex, biological maturation, body weight, body composition and physical activity (PA) in childhood. Data from QUALITY were used. Participants attended baseline (8-10 y old, n = 630) and follow-ups 2 years (n = 564) and 7 years (n = 359) after baseline. Group-based trajectory analysis for relative peak oxygen consumption (VO2peak, ml·kg-1·min-1) was performed. A multinomial logistic regression model was used to estimate the associations between baseline predictors and trajectory membership. Mean age of the 454 participants was 9.7 ± 0.9 years at baseline. Three distinct VO2peak trajectories were identified and all tended to decrease. They were labelled according to the starting point and slope. High-Decreasers were mostly boys, had lower body weight and fat-free mass index and higher PA levels at baseline (p < 0.05). Female sex and higher weight were associated with higher odds of being classified in the Low-Decreaser trajectory (OR = 74.03, 95%CI = 27.06-202.54; OR = 1.48, 95%CI = 1.36-1.60). Those with higher PA were less likely to be Low-Decreasers (OR = 0.96, 95%CI = 0.94-0.97). Sex, body weight and PA in childhood are important influencing factors of VO2peak (ml·kg-1·min-1) trajectories across adolescence.

Relationship between lifestyle habits and cardiovascular risk factors in familial hypercholesterolemia.

BACKGROUND AND AIM: Little is known about the cardioprotective potential of a healthy lifestyle in familial hypercholesterolemia (FH). The objective of this study was to evaluate the relationship between lifestyle and cardiovascular risk factors in adults with FH. METHODS AND RESULTS: This cross-sectional study leveraged data from the CARTaGENE Quebec population-based cohort (Canada). Participants with FH were identified using the validated Simplified Canadian Definition for FH. A healthy lifestyle score (HLS), ranging from 0 to 5, was calculated per adherence to 5 lifestyle habits: 1) not smoking; 2) being physically active (≥150 min/week of moderate or vigorous physical activity); 3) eating a healthy diet (Alternate Healthy Eating Index ≥50%); 4) having a light to moderate alcohol consumption (men: 1-30 g/day; women: 1-15 g/day); and 5) sleeping 7-8 h/day. Among the 122 included individuals (women, n = 78; men, n = 44; mean age ± SD: 57.3 ± 6.7 years), 92 (75.4%) had a HLS ≤3/5, while only 5 (4.1%) had a HLS of 5/5. After adjustments for sex, age, body mass index, and lipid-lowering medication use, we found no evidence of an association between the HLS and concentrations of LDL-cholesterol (ß = 0.04, 95% CI = -0.08, 0.15 mmol/L; P = 0.54). However, the HLS was favorably associated with HbA1c levels (ß = -0.07, 95% CI = -0.13, -0.01%; P = 0.02), and statistical trends suggested favorable associations with HDL-cholesterol (ß = 0.06, 95% CI = -0.02, 0.14 mmol/L; P = 0.06) and waist circumference (ß = -2.22, 95% CI = -4.62, 0.17 cm; P = 0.07). CONCLUSION: This study suggests that a healthy lifestyle is favorably associated with CVD risk factors in adults with FH.

Challenges of considering both extremities of the weight status spectrum to better understand obesity: insights from the NUTRILEAN project in constitutionally thin individuals.

BACKGROUND/OBJECTIVES: While the physiology of obesity has been so extensively investigated to date, only an extremely small number of studies (less than 50) have focused on the other extremity of the weight spectrum: constitutional thinness. Yet, this important state of underweight in the absence of any eating disorders provides a mirror model of obesity that might be particularly insightful in understanding obesity. Nevertheless, important methodological and recruitment-related issues appear when it comes to this complex constitutionally thin phenotype, as experienced by our research group with the realization of the ongoing NUTRILEAN clinical trial. To face this challenge, the present paper aims at identifying, analyzing, and discussing the quality of such recruitment processes in publications about constitutional thinness. METHODS: In this order, a group of experts collectively created a new grading system to assess the level of rigour and quality achieved by each study based on different criteria. RESULTS: The main results were that (i) metabolic-related biasing criteria were poorly observed despite being crucial, (ii) recruitment processes were not detailed enough and with sufficient explicitness, and (iii) recruiting among already identified patients would be associated with both higher sample sizes and better scores of quality. CONCLUSIONS: The present work encourages investigators to adopt a high level of rigour despite the complexity and duration of recruitment processes for this specific population, and readers to pay close attention to the quality of recruitment when interpreting the data. To better understand obesity and its physiological adaptations, it seems essential not only to compare it to normal-weight conditions, but also to the other extremity of the weight status spectrum represented by constitutional thinness.

Associations of timing of food intake with energy intake, eating behaviour traits and psychosocial factors in adults with overweight and obesity.

Introduction: Whether a late distribution of food intake impacts obesity through increased energy intake remains uncertain and the behavioural characterization of late eating needs to be further investigated. The first objective of this study was to assess the associations between late eating and body mass index (BMI) and total energy intake (TEI), and whether TEI mediates the association between late eating and BMI. The second objective was to assess the associations between late eating and eating behaviour traits or psychosocial factors and whether eating behaviour traits mediate the association between late eating and TEI. Methods: Baseline data from 301 individuals (56% women, age = 38.7 ± 8.5 years; BMI = 33.2 ± 3.4 kg/m2), who participated in four weight loss studies were used in this cross-sectional study. Total energy intake was assessed using a three-day food record from which the percentage of TEI after 17:00 and after 20:00 was calculated. Eating behaviour traits and psychosocial factors were assessed with questionnaires. Pearson correlations and mediation analyses adjusted for age, sex, underreporting of energy intake, sleep duration and bedtime were performed. Results: Percent TEI after 17:00 and after 20:00 were associated with TEI (r = 0.13, p = 0.03 for both), and TEI mediated the association between percent TEI after 17:00 and BMI (ß = 0.01 ± 0.01, 95% CI: 0.001, 0.02). Percent TEI after 17:00 was associated with disinhibition (r = 0.13, p = 0.03) and percent TEI after 20:00 was associated with susceptibility to hunger (r = 0.13, p = 0.03), stress (r = 0.24, p = 0.002) and anxiety (r = 0.28, p = 0.0004). In women, disinhibition mediated the association between percent TEI after 17:00 and TEI (ß = 3.41 ± 1.43, 95% CI: 0.92, 6.47). Susceptibility to hunger mediated the association between percent TEI after 20:00 and TEI (ß = 0.96 ± 0.59, 95% CI: 0.02, 2.34) in men and women. Conclusion: Late eating is associated with TEI and suboptimal eating behaviours which could contribute to explaining the association between timing of food intake and obesity.

Interventions to promote healthy lifestyle behaviors in children and adolescents in summer day camps: a scoping review.

BACKGROUND: Children and adolescents have suboptimal physical activity and eating habits during summer breaks. Unlike the school setting, there is little evidence on interventions to promote healthy lifestyle behaviors in Summer Day Camps (SDCs). METHODS: The aim of this scoping review was to examine physical activity, healthy eating, and sedentary behavior interventions in the SDCs. A systematic search on four platforms (EBSCOhost, MEDLINE, EMBASE, and Web of Science) was performed in May 2021 and was updated in June 2022. Studies related to promoting healthy behaviors, physical activity, sedentary behaviors and/or healthy eating among campers aged 6 to 16 in Summer Day Camps were retained. The protocol and writing of the scoping review were done according to the guidelines of the "Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for scoping reviews (PRISMA-ScR)". RESULTS: Most interventions had a positive effect on the behavioral determinants or the behaviors themselves (i.e., physical activity, sedentary behaviors, or healthy eating). Involving counsellors and parents, setting camp goals, gardening, and education are all relevant strategies in promoting healthy lifestyle behaviors in SDCs. CONCLUSIONS: Since only one intervention directly targeted sedentary behaviors, it should strongly be considered for inclusion in future studies. In addition, more long-term and experimental studies are needed to establish cause-and-effect relationships between healthy behavior interventions in SDCs and behaviors of children and young adolescents.

Genetic control of body weight by the human brain proteome.

Genome-wide association studies (GWAS) have identified hundreds of genetic variants associated with body weight but the biological relevance of most remains unexplored. Given the critical role of the brain in body weight regulation, we set out to determine whether genetic variants linked with body mass index (BMI) could be mapped to brain proteins. Using genetic colocalization, we mapped 25 loci from the largest BMI GWAS (n = 806,834) to brain protein concentrations obtained from publicly available datasets. We also performed a proteome-wide Mendelian randomization on 696 brain proteins followed by genetic colocalization and identified 35 additional brain proteins. Only a minority of these proteins (<30%) had a colocalization signal with cortex gene expression levels, highlighting the value of moving beyond gene expression levels and examining brain protein levels. In conclusion, we identified 60 unique proteins expressed in the brain that may be critical regulators of body weight in humans.

Effects of sodium intake and cardiorespiratory fitness on body composition and genetic susceptibility to obesity: results from the Quebec Family Study.

The main aim of this study was to evaluate the effects of Na intake and cardiorespiratory fitness (CRF) on body composition. The study was also intended to assess whether Na intake and/or CRF mediate the genetic susceptibility to obesity. Analyses were performed on a sample of 526 adult participants from the Quebec Family Study for whom a complete data set was available for nutrient and energy intake, CRF and body composition variables. The effects of Na, CRF and their interaction were analysed by comparing sex-specific tertiles using general linear mixed models. In both males and females, we observed a significant effect of Na intake and CRF on all body composition variables. However, in females only, we found that the effect of Na intake on body composition variables varies according to CRF level such that high Na intake was associated with increased body fatness, but only in females with low CRF. This interaction effect remained significant after statistical adjustment for total sugar, fat and energy intake. Using mediation analysis, we also found Na intake and CRF to be significant mediators of the relationship between a polygenic risk score of obesity based on > 500 000 genetic variants and BMI or waist circumference. In conclusion, the current study shows that Na intake influences body composition via mechanisms that interact with aerobic fitness, especially in females. Furthermore, both Na intake and CRF seem to be involved in the expression of the genetic susceptibility to obesity.

Lacticaseibacillus rhamnosus HA-114 improves eating behaviors and mood-related factors in adults with overweight during weight loss: a randomized controlled trial.

Background: Gut microbiota has emerged as a modifiable factor influencing obesity and metabolic diseases. Interventions targeting this microbial community could attenuate biological and psychological comorbidities of excess weight. Objective: Our aim was to determine if Lacticaseibacillus rhamnosus HA-114 supplementation accentuated beneficial impact of weight loss on metabolic and cognitive health. Methods: This 12-week randomized, double-blind, placebo-controlled trial assessed biological markers of energy metabolism, eating behaviors and mood-related factors in 152 adults with overweight receiving L. rhamnosus HA-114 supplementation or placebo, that were also on a dietary intervention inducing a controlled weight loss. Results: Although probiotic supplementation did not potentiate the reduction in body weight or fat mass, a significant decrease in plasma insulin, HOMA-IR, LDL-cholesterol and triglycerides was observed in the probiotic-supplemented group only. With respect to eating behaviors and mood-related factors, beneficial effects were either observed only in the group receiving probiotic supplementation or were significantly greater in this group, including decrease in binge eating tendencies, disinhibition and food-cravings. Conclusion: This study demonstrates the clinical relevance of probiotic supplementation to induce beneficial metabolic and psychological outcomes in individuals with overweight undergoing weight loss.Trial registration: ClinicalTrials.gov identifier: NCT02962583.

Eating behaviour traits mediate the association between satiety responsiveness and energy intake among individuals with overweight and obesity.

Whether eating behaviour traits represent factors that could explain the susceptibility to overeating in individuals with low satiety responsiveness remain to be extensively examined. This study aimed to assess if eating behaviours mediate the association between satiety responsiveness and energy intake. Baseline data from individuals with overweight or obesity (n = 303; age = 38.7 ± 8.4 years; BMI = 33.2 ± 3.4 kg/m2, 56% women) who participated in four weight-loss studies were included in this cross-sectional study. Satiety responsiveness was determined by the satiety quotient (SQ) based on fullness sensations in response to a standardized breakfast. Energy intake was self-reported in a three-day food record and measured by an ad libitum buffet meal. Eating behaviours were assessed with questionnaires. Mediation analyses adjusted for age and sex, and for underreporting for the food record, were performed using a regression-based and bootstrapping approach. The association between SQ and self-reported total energy intake was mediated by susceptibility to hunger (ß = -2.51 ± 1.26, 95% CI, -5.38 to -0.52) and its subscales, internal and external locus of hunger (ß = -2.00 ± 1.10, 95% CI, -4.50 to -0.28 and ß = -2.42 ± 1.29, 95% CI, -5.30 to -0.30, respectively). Susceptibility to hunger (ß = -2.71 ± 1.13, 95% CI, -5.29 to -0.84), internal and external locus of hunger (ß = -1.84 ± 0.95, 95% CI -4.00 to -0.30 and ß = -3.42 ± 1.31, 95% CI, -6.39 to -1.24, respectively), cues that may trigger food cravings (ß = -5.43 ± 2.91, 95% CI, -11.83 to -0.44) and state-craving as a physiological state (ß = -4.31 ± 2.51, 95%CI, -10.14 to -0.44) also mediated the association between SQ and measured energy intake. These results suggest that susceptibility to hunger and food cravings partly explained the susceptibility to overeating among individuals with low satiety responsiveness. Interventions targeting susceptibility to hunger and food cravings may thus be helpful to prevent overeating among these individuals.

Determinants of mechanical efficiency trajectories from childhood to adolescence: Findings from the QUALITY cohort.

PURPOSE: To estimate the shape and number of mechanical efficiency (ME) trajectories from childhood to adolescence; and verify whether ME trajectory membership can be predicted by sex, biological maturation, body weight, body composition and physical activity (PA) in childhood. METHODS: Data from QUALITY, an ongoing cohort study on the natural history of obesity, were used. Participants attended a baseline visit (8-10 years, n = 630) and follow-up visits two years (n = 564), and seven years (n = 377) later. ME was assessed by an incremental cycling test at 50w (ME50w, %) and at VO2peak (MEVO2peak, %). Group-based trajectory analysis for ME and a logistic regression were performed. RESULTS: Mean age of the 454 participants (boys = 54%) was 9.7 ± 0.9 years at baseline. Two distinct ME50w trajectories were identified and all tended to decrease. No distinct trajectories emerged for MEVO2peak; average MEVO2peak increased over time. Thus, the difference between MEVO2peak (∆) at baseline and follow-up was calculated for correlation analysis. Trajectory groups were labeled "Low-Decreaser" and "High-Decreaser" (Reference) for ME50w, describing the starting point and slope. High-Decreasers were mostly prepubertal girls, had lower body weight and fat free mass index, lower PA and lower VO2peak at baseline (χ2or t-test, p < 0.05). Girls were less likely to be Low-Decreasers (OR = 0.56, 95%CI = 0.42-0.74), while having overweight/obesity predicted a greater likelihood of classification in the Low-Decreaser trajectory (OR = 2.38, 95%CI = 1.16-4.88). Those with higher PA were more likely to be Low-Decreasers (OR = 1.02, 95%CI = 1.01-1.04). Finally, concerning MEVO2peak, sex, biological maturation, body weight, zBMI, fat free mass index, PA and VO2peak were positively correlated with ∆ MEVO2peak. CONCLUSIONS: We found evidence that excess weight at baseline predicts low levels of ME in childhood and adolescence. Additionally, higher PA at baseline is not related to higher ME50w levels. More research is needed to identify different approaches to explore this measure in transition to adulthood.

Estimating causal effects of physical activity and sedentary behaviours on the development of type 2 diabetes in at-risk children from childhood to late adolescence: an analysis of the QUALITY cohort.

BACKGROUND: Uncertainty remains regarding the causal effect of physical activity and sedentary behaviours on the development of type 2 diabetes in children. We aimed to estimate average treatment effects of physical activity and sedentary behaviours on risk of type 2 diabetes in individuals who are at risk during childhood and adolescence. METHODS: We used data from the Quebec Adipose and Lifestyle Investigation in Youth (QUALITY) cohort of children of western European descent (white non-Hispanic race or ethnicity) with a parental history of obesity (defined as a BMI of 30 kg/m2 or more, or a waist circumference of more than 102 cm in men and 88 cm in women) evaluated at the ages of 8-10 years (baseline), 10-12 years (first follow-up cycle), and 15-17 years (second follow-up cycle) in Québec, Canada. We measured moderate-to-vigorous physical activity (MVPA) and sedentary time by accelerometry, and leisure screen time by questionnaire at each cycle. Outcomes included fasting and 2 h post-load glycaemia and validated indices of insulin sensitivity and insulin secretion. We estimated average treatment effects of MVPA, sedentary time, and screen time on markers of type 2 diabetes using longitudinal marginal structural models with time-varying exposures, outcomes, and confounders from the ages of 8-10 to 15-17 years and inverse probability of treatment and censoring weighting. We considered both the current and cumulative effects of exposures on outcomes. FINDINGS: 630 children were evaluated at baseline (age 8-10 years) between July, 2005, and December, 2008, 564 were evaluated at the first follow-up (age 10-12 years) between July, 2007, and March, 2011, and 377 were evaluated at the second follow-up (age 15-17 years) between September, 2012, and May, 2016. Based on cumulative exposure results, estimated average treatment effects for MVPA were 5·6% (95% CI 2·8 to 8·5) on insulin sensitivity and -3·8% (-7·1 to -0·5) on second-phase insulin secretion per 10 min daily increment from the ages of 8-10 years to age 15-17 years. Average treatment effects for sedentary time and reported screen time resulted in reduced insulin sensitivity (-8·2% [-12·3 to -3·9] and -6·4% [-10·1 to -2·5], respectively), increased second-phase insulin secretion (5·9% [1·9 to 10·1] and 7·0% [-0·1 to 14·7], respectively), and higher fasting glycaemia (0·03 mmol/L [0·003 to 0·05] and 0·02 mmol/L [0·01 to 0·03], respectively) per additional daily hour from the ages of 8-10 years to 15-17 years. INTERPRETATION: Using modern causal inference approaches strengthened the evidence of MVPA and sedentary behaviours as key drivers of development of type 2 diabetes in at-risk children and adolescents, and should be considered as key targets for prevention. FUNDING: Canadian Institutes of Health Research, Heart and Stroke Foundation of Canada, and Fonds de Recherche du Québec-Santé. TRANSLATION: For the French translation of the abstract see Supplementary Materials section.

Relationship between Cardiometabolic Factors and the Response of Blood Pressure to a One-Year Primary Care Lifestyle Intervention in Metabolic Syndrome Patients.

Systemic hypertension has been recognized as a modifiable traditional cardiovascular risk factor and influenced by many factors such as eating habits, physical activity, diabetes, and obesity. The objective of this cross-sectional study was to identify factors that predict changes in blood pressure induced by a one-year lifestyle intervention in primary care settings involving a collaboration between family physicians, dietitians, and exercise specialists. Patients with metabolic syndrome diagnosis were recruited by family physicians participating in primary care lifestyle intervention among several family care clinics across Canada. Participants for whom all cardiometabolic data at the beginning (T0) and the end (T12) of the one-year intervention were available were included in the present analysis (n = 101). Patients visited the dietitian and the exercise specialist weekly for the first three months and monthly for the last nine months. Diet quality, exercise capacity, anthropometric indicators, and cardiometabolic variables were evaluated at T0 and at T12. The intervention induced a statistically significant decrease in waist circumference (WC), systolic (SBP) and diastolic (DBP) blood pressure, and plasma triglycerides, and an increase in cardiorespiratory fitness (estimated VO2max). Body weight (p < 0.001), body mass index (BMI) (p < 0.001), and fasting blood glucose (p = 0.006) reduction, and VO2max increase (p = 0.048) were all related to changes in SBP. WC was the only variable for which changes were significantly correlated with those in both SBP (p < 0.0001) and DBP (p = 0.0004). Variations in DBP were not associated with changes in other cardiometabolic variables to a statistically significant extent. Twelve participants were identified as adverse responders (AR) in both SBP and DBP and displayed less favorable changes in WC. The beneficial effects of the primary care lifestyle intervention on blood pressure were significantly associated with cardiometabolic variables, especially WC. These findings suggest that a structured lifestyle intervention in primary care can help improve cardiometabolic risk factors in patients with metabolic syndrome and that WC should be systematically measured to better stratify the patient's hypertension risk.

Comparison of different severe obesity definitions in predicting future cardiometabolic risk in a longitudinal cohort of children.

OBJECTIVES: Severe obesity (SO) prevalence varies between reference curve-based definitions (WHO: ≥99th percentile, Centers for Disease Control and Prevention (CDC): >1.2×95th percentile). Whether SO definitions differentially predict cardiometabolic disease risk is critical for proper clinical care and management but is unknown. DESIGN: Prospective cohort study SETTING: SO definitions were applied at baseline (2005-2008, Mage=9.6 years, n=548), and outcomes (fasting lipids, glucose, homoeostatic model assessment (HOMA-IR) and blood pressure) were assessed at first follow-up (F1: 2008-2011, Mage=11.6 years) and second follow-up (2015-2017, Mage=16.8 years) of the Quebec Adipose and Lifestyle Investigation in Youth cohort in Montreal, Quebec. PARTICIPANTS: Respondents were youth who had at least one biological parent with obesity. PRIMARY OUTCOME MEASURES: Unfavourable cardiometabolic levels of fasting blood glucose (≥6.1 mmol/L), insulin resistance (HOMA-IR index ≥2.0), high-density lipoprotein <1.03 mmol/L, low-density lipoprotein ≥2.6 mmol/L and triglycerides >1.24 mmol/L. Unfavourable blood pressure was defined as ≥90th percentile for age-adjusted, sex-adjusted and height-adjusted systolic or diastolic blood pressure. ANALYSIS: Area under the receiver operating characteristic curve (AUC) and McFadden psuedo R2 for predicting F1 or F2 unfavourable cardiometabolic levels from baseline SO definitions were calculated. Agreement was assessed with kappas. RESULTS: Baseline SO prevalence differed (WHO: 18%, CDC: 6.7%). AUCs ranged from 0.52 to 0.77, with fair agreement (kappa=37%-55%). WHO-SO AUCs for detecting unfavourable HOMA-IR (AUC>0.67) and high-density lipoprotein (AUC>0.59) at F1 were statistically superior than CDC-SO (AUC>0.59 and 0.53, respectively; p<0.05). Only HOMA-IR and the presence of more than three risk factors had acceptable model fit. WHO-SO was not more predictive than WHO-obesity, but CDC-SO was statistically inferior to CDC-obesity. CONCLUSION: WHO-SO is statistically superior at predicting cardiometabolic risk than CDC-SO. However, as most AUCs were generally uninformative, and obesity definitions were the same if not better than SO, the improvement may not be clinically meaningful.

The HERITAGE Family Study: A Review of the Effects of Exercise Training on Cardiometabolic Health, with Insights into Molecular Transducers.

The aim of the HERITAGE Family Study was to investigate individual differences in response to a standardized endurance exercise program, the role of familial aggregation, and the genetics of response levels of cardiorespiratory fitness and cardiovascular disease and diabetes risk factors. Here we summarize the findings and their potential implications for cardiometabolic health and cardiorespiratory fitness. It begins with overviews of background and planning, recruitment, testing and exercise program protocol, quality control measures, and other relevant organizational issues. A summary of findings is then provided on cardiorespiratory fitness, exercise hemodynamics, insulin and glucose metabolism, lipid and lipoprotein profiles, adiposity and abdominal visceral fat, blood levels of steroids and other hormones, markers of oxidative stress, skeletal muscle morphology and metabolic indicators, and resting metabolic rate. These summaries document the extent of the individual differences in response to a standardized and fully monitored endurance exercise program and document the importance of familial aggregation and heritability level for exercise response traits. Findings from genomic markers, muscle gene expression studies, and proteomic and metabolomics explorations are reviewed, along with lessons learned from a bioinformatics-driven analysis pipeline. The new opportunities being pursued in integrative -omics and physiology have extended considerably the expected life of HERITAGE and are being discussed in relation to the original conceptual model of the study.

Key process features of personalized diet counselling in metabolic syndrome: secondary analysis of feasibility study in primary care.

BACKGROUND: Personalized diet counselling, as part of lifestyle change programs for cardiometabolic risk conditions (combinations of prediabetes or type 2 diabetes, hypertension, dyslipidemia and high waist circumference) has been shown to reduce progression to type 2 diabetes overall. To identify key process of care measures that could be linked to changes in diet, we undertook a secondary analysis of a Canadian pre-post study of lifestyle treatment of metabolic syndrome (MetS). Diet counselling process measures were documented and association with diet quality changes after 3 months were assessed. Results of the primary study showed 19% reversal of MetS after 1 year. METHODS: Registered dietitians (RDs) reported on contact time, specific food behaviour goals (FBG), behaviour change techniques (BCT; adapted from the Michie CALO-RE taxonomy) and teaching resources at each contact. Diet quality was measured by 2005 Canadian Healthy Eating Index (HEI-C) and assessed for possible associations with individual BCT and FBG. RESULTS: Food behaviour goals associated with improved HEI-C at 3 months were: poultry more than red meat, increased plant protein, increased fish, increased olive oil, increased fruits and vegetables, eating breakfast, increased milk and alternatives, healthier fats, healthier snacks and increased nuts, with an adverse association noted for more use (> 2 times/ 3 months) of the balanced meal concept (F test; p < 0.001). Of 16 BCT, goal setting accounted for 15% of all BCT recorded, yet more goal setting (> 3 times/3 months) was associated with poorer HEI-C at 3 months (F test; p = 0.007). Only self-monitoring, feedback on performance and focus on past success were associated with improved HEI-C. CONCLUSIONS: These results identify key aspects of process that impact diet quality. Documentation of both FBG and BCT is highly relevant in diet counselling and a summary diet quality score is a promising target for assessing short-term counselling success.

Understanding Gene-Lifestyle Interaction in Obesity: The Role of Mediation versus Moderation.

BACKGROUND: Obesity results from complex interactions between genetic susceptibility to weight gain and poor eating and lifestyle behaviors. The approach that has been traditionally used in genetics to investigate gene-environment/lifestyle interaction in obesity is based on the concept of moderation or effect modification. Another approach called mediation analysis can be used to investigate gene-environment interaction in obesity. The objective of this review article is to explain the differences between the concepts of moderation and mediation and summarize the studies that have used mediation analysis to support the role of eating or lifestyle behaviors as putative mediators of genetic susceptibility to obesity. SUMMARY: Moderation is used to determine whether the effect of an exposure (genes associated with obesity) on an outcome (obesity phenotype) differs in magnitude and/or direction across the spectrum of environmental exposure. Mediation analysis is used to assess the extent to which the effect of the exposure on the outcome is explained by a given set of hypothesized mediators with the aim of understanding how the exposure could lead to the outcome. In comparison with moderation, relatively few studies used mediation analyses to investigate gene-environment interaction in obesity. Most studies found evidence that traits related to appetite or eating behaviors partly mediated genetic susceptibility to obesity in either children or adults. KEY MESSAGES: Moderation and mediation represent two complementary approaches to investigate gene-environment interaction in obesity and address different research questions pertaining to the cause-effect relationship between genetic susceptibility to obesity and various obesity outcomes. More studies relying on mediation are needed to better understand the role of eating and lifestyle habits in mediating genetic susceptibility to obesity.

Natural history and determinants of dysglycemia in Canadian children with parental obesity from ages 8-10 to 15-17 years: The QUALITY cohort.

In children, the mechanisms implicated in deterioration of glucose homeostasis versus reversion to normal glucose tolerance (NGT) remain uncertain. We aimed to describe the natural history of dysglycemia from childhood to late adolescence and to identify its early determinants. We used baseline (8-10 years, n = 630), 1st follow-up (10-12 years, n = 564) and 2nd follow-up (15-17 years, n = 377) data from the QUALITY cohort of White Canadian children with parental obesity. Children underwent a 2-h oral glucose tolerance test at each cycle with plasma glucose and insulin measured at 0/30/60/90/120 min. American Diabetes Association criteria defined dysglycemia (impaired fasting glucose, impaired glucose tolerance or type 2 diabetes). Longitudinal patterns of insulin sensitivity and beta-cell function were estimated using generalized additive mixed models. Model averaging identified biological, sociodemographic and lifestyle-related determinants of dysglycemia. Of the children NGT at baseline, 66 (21%) developed dysglycemia without reverting to NGT. Among children with dysglycemia at baseline, 24 (73%) reverted to NGT. In children with dysglycemia at 1st follow-up, 18 (53%) later reverted to NGT. Among biological, sociodemographic and lifestyle determinants at 8-10 years, only fasting and 2-h glucose were associated with developing dysglycemia (odds ratio [95% CI] per 1 mmol/L increase: 4.50 [1.06; 19.02] and 1.74 [1.11; 2.73], respectively). Beta-cell function decreased by 40% in children with overweight or obesity. In conclusion, up to 75% of children with dysglycemia reverted to NGT during puberty. Children with higher fasting and 2-h glucose were at higher risk for progression to dysglycemia, while no demographic/lifestyle determinants were identified.