Evidence map›Paper›PMID 36115992›Full record

ArticleInternational journal of health geographics2022

Comparing effects of Euclidean buffers and network buffers on associations between built environment and transport walking: the Multi-Ethnic Study of Atherosclerosis.

Jingjing Li, Adam Peterson, Amy H Auchincloss, Jana A Hirsch, Daniel A Rodriguez, Steven J Melly, Kari A Moore, Ana V Diez-Roux, Brisa N Sánchez

Open access · goldAbstract read
In one paragraph

Article in International journal of health geographics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
3.8field-weighted citation impact, top 8% 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

11 citing papers in PubMed, 1 synthesis or guideline pooled it, 18 citations in OpenAlex.

  1. Pooled it
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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 4 institutions in 2 countries.

Jingjing LiDepartment of Land Resources Management, School of Public Administration, China University of Geosciences, 388 Lumo Rd., Hubei, 430074, Wuhan, China. lijingjing@cug.edu.cn.
Adam PetersonDepartment of Biostatistics, the University of Michigan, 1415 Washington Heights, Ann Arbor, MI, 48109, USA.
Amy H AuchinclossUrban Health Collaborative, Dornsife School of Public Health, Drexel University, 3600 Market St. 7th Floor, PA, 19104, Philadelphia, USA.
Jana A HirschUrban Health Collaborative, Dornsife School of Public Health, Drexel University, 3600 Market St. 7th Floor, PA, 19104, Philadelphia, USA.
Daniel A RodriguezDepartment of City & Regional Planning and Institute for Transportation Studies, University of California Berkeley, 230 Wurster Hall #1820, Berkeley, CA, 94720, USA.
Steven J MellyUrban Health Collaborative, Dornsife School of Public Health, Drexel University, 3600 Market St. 7th Floor, PA, 19104, Philadelphia, USA.
Kari A MooreUrban Health Collaborative, Dornsife School of Public Health, Drexel University, 3600 Market St. 7th Floor, PA, 19104, Philadelphia, USA.
Ana V Diez-RouxUrban Health Collaborative, Dornsife School of Public Health, Drexel University, 3600 Market St. 7th Floor, PA, 19104, Philadelphia, USA.
Brisa N SánchezDepartment of Epidemiology and Biostatistics, Dornsife School of Public Health, Drexel University, 3215 Market St, Nesbitt HallPhiladelphia, PA, 19104, USA.
Drexel University · USChina University of Geosciences · CNUniversity of California, Berkeley · USUniversity of Michigan–Ann Arbor · US

Funding

Institute for Clinical and Translational ResearchUL1TR001079 · NCATS · JOHNS HOPKINS UNIVERSITY · PI FORD, DANIEL ERNEST · 2013 to 2017
$60.1M
Clinical and Translational Science AwardUL1TR000040 · NCATS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI GINSBERG, HENRY N · 2012 to 2015
$26.2M
Neighborhoods and CVD Risk in a Multiethnic Cohort (RMI)R01HL071759 · NHLBI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI DIEZ ROUX, ANA VICTORIA · 2003 to 2013
$4.8M
Characterizing health impacts of built environment features using complex dataR01HL131610 · NHLBI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI SANCHEZ, BRISA N · 2017 to 2021
$3.6M
Communities Designed to Support Cardiovascular Health for Older AdultsR01AG049970 · NIA · DREXEL UNIVERSITY · PI LOVASI, GINA S · 2015 to 2018
$2.8M
ConProject-003R56AG049970 · NIA · DREXEL UNIVERSITY · PI LOVASI, GINA S · 2022 to 2023
$1.3M
NCATS NIH HHS UL1 TR000040NCATS NIH HHS UL1 TR001079NHLBI NIH HHS R01 HL071759NHLBI NIH HHS R01 HL131610NIA NIH HHS R01 AG049970NIA NIH HHS R56 AG049970
6 · The paper itself

Abstract

backgroundTransport walking has drawn growing interest due to its potential to increase levels of physical activities and reduce reliance on vehicles. While existing studies have compared built environment-health associations between Euclidean buffers and network buffers, no studies have systematically quantified the extent of bias in health effect estimates when exposures are measured in different buffers. Further, prior studies have done the comparisons focusing on only one or two geographic regions, limiting generalizability and restricting ability to test whether direction or magnitude of bias are different by context. This study aimed to quantify the degree of bias in associations between built environment exposures and transport walking when exposures were operationalized using Euclidean buffers rather than network buffers in diverse contexts.

methodsWe performed a simulations study to systematically evaluate the degree of bias in associations between built environment exposures in Euclidean buffers and network buffers and transport walking, assuming network buffers more accurately captured true exposures. Additionally, we used empirical data from a multi-ethnic, multi-site cohort to compare associations between built environment amenities and walking for transport where built environment exposures were derived using Euclidean buffers versus network buffers.

resultsSimulation results found that the bias induced by using Euclidean buffer models was consistently negative across the six study sites (ranging from -80% to -20%), suggesting built environment exposures measured using Euclidean buffers underestimate health effects on transport walking. Percent bias was uniformly smaller for the larger 5 km scale than the 1 km and 0.25 km spatial scales, independent of site or built environment categories. Empirical findings aligned with the simulation results: built environment-health associations were stronger for built environment exposures operationalized using network buffers than using Euclidean buffers.

conclusionThis study is the first to quantify the extent of bias in the magnitude of the associations between built environment exposures and transport walking when the former are measured in Euclidean buffers vs. network buffers, informing future research to carefully conceptualize appropriate distance-based buffer metrics in order to better approximate real geographic contexts. It also helps contextualize existing research in the field that used Euclidean buffers when that were the only option. Further, this study provides an example of the uncertain geographic context problem.

Indexed as

AtherosclerosisResidence CharacteristicsBuilt EnvironmentEthnicityHumansWalkingBuilt environmentEuclidean buffersNetwork buffersSimulationTransport walking

Identifiers

PMID36115992
PMCPMC9482303
OpenAlexW4296248377

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.