Associations of the perceived neighborhood environment and screen time in adolescents living in a medium-sized city in Brazil: a cross-sectional study

Physical and social neighborhood disorder in Latin American cities: a scoping review

Neighborhood disorder is an important aspect that may influence the health of residents in urban areas. The aims of this study were to map and systematize methods for measuring physical and social neighborhood disorder in studies conducted in Latin American cities. By means of a scoping review, articles published from 2000 in English, Spanish, and Portuguese with the following descriptors were mapped: neighborhood, physical disorder, and social disorder. Searches were conducted in MEDLINE (PubMed), LILACS (Virtual Health Library), Scopus, Web of Science, and Cochrane Library. Information on authorship, year, study type, locality, data source, target population, outcome, dominion, indicator, method, geographic unit, and unit of analysis was extracted. Variables from the disorder-related studies were extracted and grouped by similarity of content and themes. A total of 22 articles were identified, all published between 2012 and 2022, the majority in Brazil (n = 16). The perception of the individual was the most used method. The most frequent theme addressed in the physical disorder dominion was public streets (n = 20) and security (n = 15), in the social disorder dominion. A lack of consensus in the literature regarding variables used to measure physical and social neighborhood disorder in Latin American cities was detected. In addition to the need for standardization of the theme, studies to verify the sustainability of proposed measurement methods relevant to dynamically classify and compare urban neighborhoods and health impacts based on levels of exposure to physical and social disorder, are recommended.

Greenspace and mortality in the U.K. Biobank: Longitudinal cohort analysis of socio-economic, environmental, and biomarker pathways

Exposure to natural greenspace benefits health through direct and indirect pathways: increasing physical activity, improving mental health, relieving social isolation, reducing exposure to extreme temperature, noise, and air pollution. Understanding the etiologic pathway of greenspace and health is needed. Here, we used a large cohort follow-up data from the U.K. Biobank to quantify the magnitude of behavioural factors, psychological factors, biomarkers/physiological measurements, co-morbid diseases, and environmental exposure as potential mediators in the relationship between greenspace and mortality. We estimated hazard ratios (HR) with Cox proportional hazards models, and undertook exploratory mediation analyses to quantify the relative contribution of five types of mediators. Our results indicate greenspace was strongly associated with lower mortality risks [per IQR of public greenspace (HR = 0.90 (95% CI 0.86-0.84)) and domestic gardens (HR = 0.91, (95% CI 0.88-0.94))]. The protective associations were especially pronounced among those with lower individual-level socioeconomic status or living in places with area-level deprivation. Exploratory mediation analysis detected benefits in pathways through reducing air pollution, relieving social isolation and depression, increased physical activity and time spent outdoor, better lung function (FEV1/FVC), and having higher serum vitamin D levels.

Association between screen time and accelerometer-measured 24-h movement behaviors in a sample of Brazilian adolescents

OBJECTIVES

Different screen time activities may be related to sleep, physical activity, and sedentary behavior. The objective was to examine the association between self-reported screen time activities and accelerometer-measured 24-h movement behaviors.

STUDY DESIGN

This was a cross-sectional study.

METHODS

Adolescents' (n = 718, 50.4% girls, 16 years) sleep duration, sedentary behavior, light-intensity physical activity (LPA), and moderate-to-vigorous physical activity (MVPA) were estimated with wrist-worn accelerometry. Time spent on screen time activities related to studying, working, watching videos, playing video games, and using social media was self-reported. Multilevel linear regressions were used to test the association between screen time with sleep, sedentary behavior, and physical activity.

RESULTS

Boys and girls slept 6.4 and 6.7 h per night, spent 10.4 and 10.1 h/d in sedentary behavior, spent 4.0 and 4.4 h/d in LPA, and spent 34.7 and 29.2 min/d in MVPA, respectively. Studying was inversely related to LPA and MVPA. Working was inversely related to sleep and positively related to LPA. Watching videos was associated with lower LPA and MVPA. For boys, videogames were associated with increased sedentary behavior and lower LPA and MVPA. For girls, studying and/or using social media were associated with lower LPA and MVPA.

CONCLUSIONS

Indicators of screen time were associated with different accelerometer-measured 24-h movement behaviors in this sample of Brazilian adolescents.

Disentangling individual, school, and neighborhood effects on screen time among adolescents and young adults in the United States

OBJECTIVES

To examine the association between individual, neighborhood, and school-level influences on individual screen time among adolescents and young adults (AYAs) in the National Longitudinal Study of Adolescent to Adult Health.

METHODS

We classified screen time continuously as self-reported total hours per week of television, videos, and video/computer games at baseline and categorical as extended screen time (≥14 h per week). We fit cross-classified multilevel models (CCMM) to examine to examine the individual-, school- and neighborhood-level demographic and socioeconomic factors associated with screen time. Models were fit using MLwiN with Bayesian estimation procedures.

RESULTS

AYAs reported an average of 22.8 (SD = 19.4) and 21.9 (SD = 20.3) hours of screen time, respectively. At the individual level, younger age, male sex, Black/multiracial race, receipt of public assistance, and lower parental education were associated with higher screen time. At the school level, being out of session (i.e., school and national holidays including summer), having a higher proportion of non-White students, and having a lower proportion of parents with a college education were associated with higher individual screen time.

CONCLUSIONS

We found that individual-level factors most influence youth screen time, with smaller contributions from school factors.

Correlates of screen time and mediators of differences by parental education among adolescents

Background

Existing literature shows that there is an inverse association between socioeconomic position and screen time among adolescents. What is less known is the mechanism behind these differences. The study aimed to explore individual, interpersonal and neighborhood environmental correlates of total screen time (TST) among adolescents and to assess their mediating role in the association between parental education and TST.

Methods

A cross-sectional study including 706 adolescents (mean age of 13.6 (SD = 0.3)) was used to collect data at schools through an online questionnaire. Multiple regression analyses were used to explore factors associated with TST. Mediation analyses were conducted to assess whether these factors mediated the association between parental education and TST.

Results

Multiple linear regression analyses, adjusted for gender and age, showed that parental modelling of TV and movie streaming, TV/movie streaming during dinner and access to screens were positively related to TST. Self-efficacy towards limiting TV and movie streaming, self-efficacy towards limiting computer/electronic game use, and the perceived opportunities for physical activity in the neighborhood were inversely related to total screen time. All of these factors except self-efficacy towards limiting TV and movie streaming mediated the association between parental education and TST.

Conclusions

The study identified several modifiable factors at the individual, interpersonal and neighborhood environmental levels that can be targeted in interventions aimed at decreasing screen time among youth in general and among those with a low socioeconomic position in particular.