Evidence map›Paper›PMID 32368490›Full record

ArticleJournal of transport & health2020

Associations between body mass index, physical activity and the built environment in disadvantaged, minority neighborhoods: Predictive validity of GigaPan® imagery.

Cathy Antonakos, Ross Baiers, Tamara Dubowitz, Philippa Clarke, Natalie Colabianchi

Abstract read
In one paragraph

Article in Journal of transport & health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

5 authors.

Cathy AntonakosEnvironment and Policy Lab, School of Kinesiology, University of Michigan, Ann Arbor, MI, USA.
Ross BaiersEnvironment and Policy Lab, School of Kinesiology, University of Michigan, Ann Arbor, MI, USA.
Tamara DubowitzRAND Corporation, Pittsburgh, PA, USA.
Philippa ClarkeDepartment of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA.
Natalie ColabianchiEnvironment and Policy Lab, School of Kinesiology, University of Michigan, Ann Arbor, MI, USA.

Funding

Impact of Greenspace Improvement on Physical Activity in a Low Income CommunityR01CA164137 · NCI · RAND CORPORATION · PI DUBOWITZ, TAMARA · 2012 to 2016
$3.1M
Improving environmental measures in obesity research using innovative technologyR21CA188481 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI COLABIANCHI, NATALIE · 2015 to 2016
$397k
NCI NIH HHS R01 CA164137NCI NIH HHS R21 CA188481
6 · The paper itself

Abstract

backgroundThe built environment has been shown to influence health in studies of disadvantaged populations using different measurement methods. This study determined whether environmental exposures derived from GigaPan® images could serve as valid predictors of body mass index (BMI), walking and moderate to vigorous physical activity (MVPA) in a longitudinal study of low-income adults living in two primarily African American neighborhoods in Pittsburgh, Pennsylvania, USA. GigaPan® is a robotic system used to obtain high-resolution, panoramic images of environments.

methodsMicroscale environmental features along 481 streets were audited in 2015-2016 using an audit form. Environmental exposures were estimated for 731 adult participants, using a sample of street segments within a 0.4 km (0.25 mile) network distance from each participant's residential address. Summary environmental exposures were constructed using factor analysis. We tested associations between participant-level environmental exposures and objectively measured BMI, self-reported walking and objectively measured MVPA in regression models controlling for baseline health and demographic variables.

resultsThree factors representing participants' environmental exposures were constructed: pedestrian bicycle-amenities; hilly-vacant-boarded; physical activity-recreation/low housing density. Environments with infrastructure and amenities supportive of walking and bicycling were associated with lower BMI (Coef. = ‒0.47, p = 0.02). Frequent walking was less likely in environments with more physical activity and recreation venues/low housing density (OR = 0.81, 95% CI [0.67, 0.96]). MVPA was not associated with any of the environmental measures and the hilly-vacant-boarded factor was not associated with any of the outcomes.

conclusionsPredictive validity was demonstrated for an environmental exposure factor that captured features supportive of walking and cycling in a model predicting BMI, using built environment audit data from GigaPan® imagery. A complementary analysis found lower odds of frequent walking in the neighborhood among participants with exposure to more physical activity and recreational features, but fewer types and lower density of housing.

Identifiers

PMID32368490
PMCPMC7196415

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.