Prospective associations between neighborhood features and body mass index in Montreal adolescents.

PURPOSE: To investigate the association between the neighborhood built environment and trajectories of body mass index (BMI) in youth. METHODS: Data were collected in a prospective study of 1293 adolescents in Montreal. Built environment variables were obtained from public databases for road networks, land use, and the Canadian Census. Anthropometric data were collected when participants were ages 12.5, 15 and 17 years. We undertook hierarchical cluster analysis to identify contrasting neighborhood types based on features of the built environment (e.g., vegetation, population density, walkability). Associations between neighborhood type and trajectories of BMI z-score (BMIz) were estimated using multivariable linear mixed regression analyses, stratified by sex. RESULTS: We identified three neighborhood types: Urban, Suburban, and Village. In contrast to the Urban type, the Suburban type was characterized by more vegetation, few services and low population density. Village and Suburban types were similar, but the former had greater land use diversity, population density with more parks and a denser food environment. Among girls, living in Urban types was associated with decreasing BMIz trajectories. Living in Village types was associated with increasing BMIz trajectories. No associations were observed among boys. CONCLUSIONS: Neighborhoods characterized by greater opportunities for active living appear to be less obesogenic, particularly among girls.

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.

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.

Physical Activity, Screen Time, and Sleep Trajectories From Childhood to Adolescence: The Influence of Sex and Body Weight Status.

BACKGROUND: Behavioral trajectories from childhood to adolescence may differ and are poorly understood. The authors estimated the trajectories of moderate to vigorous physical activity (MVPA), screen time, and sleep duration during this period, by sex and initial weight status. METHODS: Data from Quebec Adiposity and Lifestyle Investigation in Youth, an ongoing cohort study in Canada on the natural history of obesity, were used. Participants predisposed to obesity attended baseline (8-10 y old, n = 630) and follow-up visits 2 years (n = 564) and 7 years (n = 359) after baseline. Participants with completed self-reported and accelerometer-based data were included in the analyses (n = 191, 353, and 240 for MVPA, screen time, and sleep, respectively). The authors performed group-based trajectory analyses and multinomial logistic regression models. RESULTS: Two MVPA, 3 screen time, and 2 sleep trajectories were identified. Girls were more likely than boys to belong to trajectory with lower MVPA means (odds ratio [OR] = 6.45; 95% confidence interval [CI], 3.08 to 13.49), yet less likely to belong to the trajectory with higher screen time (OR = 0.47; 95% CI, 0.23 to 0.97) and lower sleep duration (OR = 0.46; 95% CI, 0.27 to 0.78). Overweight or obesity at baseline was associated with a greater likelihood of belonging to the trajectory with lower MVPA (OR = 10.99; 95% CI, 1.31 to 91.14) and higher screen time (OR = 2.01; 95% CI, 1.04 to 4.06), respectively. CONCLUSIONS: It appears to be gender- and weight-based determinants of behavioral trajectories in this sample. These results may provide guidance for interventions in similar populations.

Reduction in ambulatory distance from childhood through adolescence: The impact of the number and length of steps.

BACKGROUND: The aim of this study was to explore the relationship between ambulatory distance with steps/day and increased step length as children age. METHODS: This is a prospective cohort study. Forty-five children from the QUALITY cohort were assessed at childhood (baseline) and seven years later during adolescence (follow-up). Daily step count was evaluated by accelerometry, step length by a standardized test, and daily ambulatory distance was calculated based on step count and length. RESULTS: Children grew by an average of 0.33 m from childhood to adolescence (p < 0.001). The daily ambulatory distance decreased by an average 3008 m from childhood to adolescence (p < 0.001). Step length increased an average of 0.10 m (p < 0.001) from childhood to adolescence, while the number of steps taken decreased by an average of 5549 steps (childhood to adolescence) (p < 0.001). The change in the number of steps between childhood and adolescence represents 84.6% of the change in the ambulatory distance while the change in step length explained an additional 13.0. CONCLUSIONS: The decrease in the ambulatory distance from childhood to adolescence was strongly explained by the decrease in step count; however the increase in step length should not to be neglected.