Neighborhood built environment and socio-economic status in relation to multiple health outcomes in adolescents

Journal of School Health

2018

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BACKGROUND:The purpose of this study was to: (1) describe modes of transport to school, with a specific focus on the use of public bicycle share programs (PBSP); and (2) assess sociodemographic, psychosocial, and environmental correlates of bike and PBSP use to go to school. METHODS:A group of 465 adolescents from the International Physical Activity and the Environment Network (IPEN) Adolescent Study (Valencia, Spain) participated in the research. Mixed regression analyses were conducted on the data obtained. RESULTS:Not having bicycle access, a PBSP card, or a public bike lane close to the school is negatively associated with bicycle use. PBSP is positively associated with physical self-efficacy and bicycle availability and negatively associated with the number of vehicles per drivers at home and not having PBSP stations close to the school. CONCLUSIONS:The strongest predictive factor, as regards cycling as an active mode of transport to school among adolescents is having a PBSP card. Schools have a crucial role in promoting bicycle use through collaboration when designing public policies that consider access to bike lane networks and PBSP stations and therefore should encourage local government implementation policies and/or increase PBSP stations within 250 m of the school.Citation: Estevan I, Queralt A, Molina-García J. Biking to school: the role of bicycle-sharing programs in adolescents.

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Biking to School: The Role of Bicycle‐Sharing Programs in Adolescents

Estevan

Queralt

Journal of School Health

2018

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“…Moreover, most studies analysed separately the home or school-built environment or the home-school route, but very few studied several built environments (e.g., [22]). In addition, since the built environment is highly contextual and differs in every country, more research is needed in Spain since there are few studies about the built environment and ACS [23][24][25]. For example, the study of Rodríguez-López et al (2017) [26], that used the same Spanish urban sample as in the current study, only studied the distance from home to school but they did not include any home or school neighbourhood variables.…”

Section: Acs Behaviourmentioning

confidence: 97%

“…Mitra et al (2010) [31] observed that the density of industrial (manufacturing/trade) and office employment had a high and negative association with ACS to/from school in adolescents, while retail and service employment had no association with ACS. In addition, there is evidence of more ACS trips for children attending schools located in lower socio-economic status (SES) neighbourhoods [23,32], and more obesity and body fat for adolescents from lower-SES home neighbourhoods [24]. However, Ikeda et al (2018a) [32] found that ACS was negatively associated with school SES for youths.…”

Section: Environmental Factors That May Influence Acs Of Children Andmentioning

confidence: 99%

A GIS-Based Method for Analysing the Association Between School-Built Environment and Home-School Route Measures with Active Commuting to School in Urban Children and Adolescents

Campos-Sánchez

Abarca-Álvarez

et al. 2020

IJERPH

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In the current call for a greater human health and well-being as a sustainable development goal, to encourage active commuting to and from school (ACS) seems to be a key factor. Research focusing on the analysis of the association between environmental factors and ACS in children and adolescents has reported limited and inconclusive evidence, so more knowledge is needed about it. The main aim of this study is to examine the association between different built environmental factors of both school neighbourhood and home-school route with ACS of children and adolescents belonging to urban areas. The ACS level was evaluated using a self-reported questionnaire. Built environment variables (i.e., density of residents, street connectivity and mixed land use) within a school catchment area and home-school route characteristics (i.e., distance and pedestrian route directness—PRD) were measured using a geographic information system (GIS) and examined together with ACS levels. Subsequently, the association between environmental factors and ACS was analysed by binary logistic regression. Several cut-off points of the route measures were explored using receiver operating characteristic (ROC) curves. In addition, the PRD was further studied regarding different thresholds. The results showed that 70.5% of the participants were active and there were significant associations between most environmental factors and ACS. Most participants walked to school when routes were short (distance variable in children: OR = 0.980; p = 0.038; and adolescents: OR = 0.866; p < 0.001) and partially direct (PRD variable in children: OR = 11.334; p < 0.001; and adolescents: OR = 3.513; p < 0.001), the latter specially for children. Mixed land uses (OR = 2.037; p < 0.001) and a high density of street intersections (OR = 1.640; p < 0.001) clearly encouraged adolescents walking and slightly discouraged children walking (OR = 0.657, p = 0.010; and OR = 0.692, p = 0.025, respectively). The assessment of ACS together with the environmental factors using GIS separately for children and adolescents can inform future friendly and sustainable communities.

“…Macro-scale GIS analytical procedures for the present study have been described in detail elsewhere [17]. Briefly, intersection density (junctions/km 2 ), residential density (residences/km 2 ), land use mix (ranges between 0 and 1; homogeneity and heterogeneity in land uses, respectively) and a composite walkability index (calculated as the z-scores of intersection density, residential density and land use mix) [46] were computed for each SN-BE. GIS-derived variables were applied to a 0.5 km street-network buffer-zone around each school (detailed polygon-generated service areas, no trim) and corresponded to the street-network buffer-zone distance used in MAPS Global audits.…”

Section: Macro-scale Gis Analysis Of the School Neighbourhood Built Ementioning

confidence: 99%

School Neighbourhood Built Environment Assessment for Adolescents’ Active Transport to School: Modification of an Environmental Audit Tool and Protocol (MAPS Global-SN)

Pocock

Moore

et al. 2020

IJERPH

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School neighbourhood built environments (SN-BE) can influence adolescents’ active transport to school habits. Typically, SN-BE assessment has involved micro-scale (i.e., environmental audits) or macro-scale (Geographic Information Systems (GIS)) assessment tools. However, existing environmental audits are time/resource-intensive and not specific to school neighbourhoods, while GIS databases are not generally purposed to include micro-scale data. This study evaluated the inter-rater reliability and feasibility of using a modified audit tool and protocol (Microscale Audit of Pedestrian Streetscapes Global–School Neighbourhood (MAPS Global-SN)) to assess the SN-BE of twelve secondary schools in Dunedin, New Zealand. Correlations between MAPS Global-SN and GIS measures of the SN-BE were also examined. Specifically, MAPS Global-SN audit and GIS spatial analysis (intersection density, residential density, land use mix, walkability) was conducted within a 0.5 km street-network buffer-zone around all twelve schools. Based on investigator and expert consultation, MAPS Global-SN included eight modifications to both auditing processes and items. Inter-rater reliability data was collected from two independent auditors across two schools. The feasibility of a condensed audit protocol (auditing one side of each street segment in the neighbourhood, compared to both sides) was also assessed. Results indicated the modified MAPS Global-SN tool had good to excellent inter-rater reliability and the condensed MAPS Global-SN audit protocol appeared to sufficiently represent the micro-scale SN-BE. Results also highlighted the complementary nature of micro- and macro-scale assessments. Further recommendations for SN-BE assessment are discussed.