No abstract

In recent years, the role of neighbourhoods has been increasingly investigated with respect to obesity in children. [1][2][3] Neighbourhood built environments may promote childhood obesity by favouring antecedent behaviours, including physical inactivity and unhealthful diets. Compared with physical activity, fewer studies have addressed children's diets. 1 Most studies examining associations between local neighbourhood availability of food establishments and residents' diets have focused on adults. 4 Overall, findings from studies involving children are less consistent, notably for associations between access to supermarkets and vegetable and fruit (V&F) intake. [5][6][7] Greater access to convenience stores, which typically offer limited fresh produce, has been found to be associated with lower V&F intake 5,7 and higher intake of sweet/salty snacks 6 and sugar-sweetened beverages 8 in youth. Although some studies have reported associations between the availability of fast-food restaurants near children's residence and their diets, 7,8 others do not support such findings. 6,9,10 Given the conflicting results in the literature, there is a need to clarify the relation between neighbourhood food environments and children's diets.In addition to residential neighbourhoods, school neighbourhood environments are relevant activity spaces and should be investigated in relation to obesity-related behaviours in children. 11,12 During the academic year, travel to and from school exposes children to school neighbourhood food environments. Recently, policies have targeted in-school food environments, but initiatives aimed at regulating food opportunities in school neighbourhoods have yet to be widely implemented. Fast-food restaurants and convenience stores are known to cluster within short distances from schools. 13,14 However, it is not clear to what extent the availability of the latter is associated with children's diet. 2,9

Road traffic and related noise is a major source of annoyance and impairment to health in urban areas. Many areas exposed to road traffic noise are also exposed to rail and air traffic noise. The resulting annoyance may depend on individual/neighborhood socio-demographic factors. Nevertheless, few studies have taken into account the confounding or modifying factors in the relationship between transportation noise and annoyance due to road traffic. In this study, we address these issues by combining Geographic Information Systems and epidemiologic methods. Street network buffers with a radius of 500 m were defined around the place of residence of the 7290 participants of the RECORD Cohort in Ile-de-France. Estimated outdoor traffic noise levels (road, rail, and air separately) were assessed at each place of residence and in each of these buffers. Higher levels of exposure to noise were documented in low educated neighborhoods. Multilevel logistic regression models documented positive associations between road traffic noise and annoyance due to road traffic, after adjusting for individual/neighborhood socioeconomic conditions. There was no evidence that the association was of different magnitude when noise was measured at the place of residence or in the residential neighborhood. However, the strength of the association between neighborhood noise exposure and annoyance increased when considering a higher percentile in the distribution of noise in each neighborhood. Road traffic noise estimated at the place of residence and road traffic noise in the residential neighborhood (75th percentile) were independently associated with annoyance, when adjusted for each other. Interactions of effects indicated that the relationship between road traffic noise exposure in the residential neighborhood and annoyance was stronger in affluent and high educated neighborhoods. Overall, our findings suggest that it is useful to take into account (i) the exposure to transportation noise in the residential neighborhood rather than only at the residence, (ii) different percentiles of noise exposure in the residential neighborhood, and (iii) the socioeconomic characteristics of the residential neighborhood to explain variations in annoyance due to road traffic in the neighborhood.

The effect of screen time during secondary school on percent body fat was examined in a cohort of 744 Canadian adolescents aged 12-13 years at baseline. Participants completed self-reported questionnaires on television viewing and computer use in 19 survey cycles over 57 months from 1999 to 2005. Triceps skinfold thickness and subscapular skinfold thickness were measured in survey cycles 1 and 19. Four screen-time trajectory groups identified in growth mixture modeling included steady-low screen time (73% of the sample), steady-high (10%), increasers (9%), and decreasers (8%). The effect of screen-time trajectory on percent body fat at survey cycle 19 was modeled in boys and girls separately by using linear regression, adjusting for baseline percent body fat and physical activity. Relative to that of steady-low screen-time trajectory group boys, percent body fat was 2.9 (95% confidence interval: 0.7, 5.0) and 2.4 (95% confidence interval: 0.5, 4.2) percentage units higher on average among "increasers" and "steady-high" trajectory group boys, respectively. There was no evidence that screen time has an effect on percent body fat in girls overall, although physical activity modified the association between screen time and percent body fat in both sexes. Efforts to prevent obesity in youth should emphasize reducing screen time.

Summary Background The 24‐hour movement guidelines provide recommendations for physical activity, screen time and sleep duration for children. Objectives Describe adherence to the guidelines and their cross‐sectional and longitudinal associations with adiposity from childhood to adolescence. Methods Data are from the QUALITY Cohort. Children were followed at 8 to 10 years (childhood; n = 630), 10 to 12 years (early adolescence; n = 564) and 15 to 17 years (adolescence; n = 377). Physical activity, screen time, and sleep duration were measured by accelerometry and questionnaires. Body mass index z‐scores (zBMI), waist circumference, waist‐to‐height ratio and percent body fat were based on clinical measurements. Multiple linear regressions estimated associations. Results In childhood, early adolescence and adolescence, 14%, 6%, and 0% of participants met the 24‐hour movement guidelines, respectively. Meeting fewer guideline components was cross‐sectionally associated with higher adiposity at each visit. Meeting fewer guideline components in childhood was longitudinally associated with higher adiposity at later visits. For example, those meeting none of the guideline components (vs all) in childhood had a 1.66 SD (95% CI: 0.42, 2.89) higher zBMI in early adolescence. Conclusion Few participants met the guidelines. Not meeting the guidelines in childhood is associated with higher adiposity 2 and 7 years later. Interventions are needed to increase adherence to the 24‐hour movement guidelines across childhood and adolescence.

Migration status, source region, and time since migration are informative migration indicators for cesarean section risk.

Findings indicate that some shared neighborhood exposures are associated with greater risk of obesity for entire families whereas other exposures may heighten obesity risk in some but not all family members. Patterns may reflect differences in the way in which family members use residential neighborhood environments.

No abstract