Evidence map›Paper›PMID 32456114›Full record

ArticleInternational journal of environmental research and public health2020

Google Street View Derived Built Environment Indicators and Associations with State-Level Obesity, Physical Activity, and Chronic Disease Mortality in the United States.

Lynn Phan, Weijun Yu, Jessica M Keralis, Krishay Mukhija, Pallavi Dwivedi, Kimberly D Brunisholz, Mehran Javanmardi, Tolga Tasdizen, Quynh C Nguyen

Open access · goldAbstract read
In one paragraph

Article in International journal of environmental research and public health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 1 pooled it
3.0field-weighted citation impact, top 9% of its field
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

19 citing papers in PubMed, 1 synthesis or guideline pooled it, 31 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 3 institutions in 1 country.

Lynn PhanDepartment of Public Health Science, University of Maryland School of Public Health, College Park, MA 20742, USA.
Weijun YuDepartment of Epidemiology and Biostatistics, University of Maryland School of Public Health, College Park, MD 20742, USA.ORCID 0000-0002-0771-5581
Jessica M KeralisDepartment of Epidemiology and Biostatistics, University of Maryland School of Public Health, College Park, MD 20742, USA.ORCID 0000-0003-3178-180X
Krishay MukhijaThe Harker School, San Jose, CA 95129, USA.
Pallavi DwivediDepartment of Epidemiology and Biostatistics, University of Maryland School of Public Health, College Park, MD 20742, USA.
Kimberly D BrunisholzIntermountain Healthcare Delivery Institute, Intermountain Healthcare, Murray, UT 4107, USA.
Mehran JavanmardiDepartment of Electrical and Computer Engineering, Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT 84112, USA.
Tolga TasdizenDepartment of Electrical and Computer Engineering, Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT 84112, USA.
Quynh C NguyenDepartment of Epidemiology and Biostatistics, University of Maryland School of Public Health, College Park, MD 20742, USA.ORCID 0000-0003-4745-6681
University of Maryland, College Park · USUniversity of Utah · USIntermountain Healthcare · US

Funding

Utah Center for Clinical and Translational ScienceUL1TR002538 · NCATS · UNIVERSITY OF UTAH · PI HESS, RACHEL, MAJERSIK, JENNIFER JUHL · 2018 to 2022
$26.0M
Neighborhood Looking Glass: 360 Degree Automated Characterization of the Built Environment for Neighborhood Effects ResearchR01LM012849 · NLM · UNIV OF MARYLAND, COLLEGE PARK · PI NGUYEN, QUYNH · 2018 to 2021
$1.3M
NCATS NIH HHS UL1 TR002538NIH HHS R01 LM012849NLM NIH HHS R01 LM012849
6 · The paper itself

Abstract

Previous studies have demonstrated that there is a high possibility that the presence of certain built environment characteristics can influence health outcomes, especially those related to obesity and physical activity. We examined the associations between select neighborhood built environment indicators (crosswalks, non-single family home buildings, single-lane roads, and visible wires), and health outcomes, including obesity, diabetes, cardiovascular disease, and premature mortality, at the state level. We utilized 31,247,167 images collected from Google Street View to create indicators for neighborhood built environment characteristics using deep learning techniques. Adjusted linear regression models were used to estimate the associations between aggregated built environment indicators and state-level health outcomes. Our results indicated that the presence of a crosswalk was associated with reductions in obesity and premature mortality. Visible wires were associated with increased obesity, decreased physical activity, and increases in premature mortality, diabetes mortality, and cardiovascular mortality (however, these results were not significant). Non-single family homes were associated with decreased diabetes and premature mortality, as well as increased physical activity and park and recreational access. Single-lane roads were associated with increased obesity and decreased park access. The findings of our study demonstrated that built environment features may be associated with a variety of adverse health outcomes.

Indexed as

Built EnvironmentExerciseObesityResidence CharacteristicsChronic DiseaseEnvironment DesignHumansMortalityUnited Statesbig databuilt environmentcardiovascular diseasediabetesgoogle street viewmortalityobesityphysical activity

Identifiers

PMID32456114
PMCPMC7277659
OpenAlexW3026759385

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.