Evidence map›Paper›PMID 33976378›Full record

ArticleInternational journal of obesity (2005)2021

Does the built environment have independent obesogenic power? Urban form and trajectories of weight gain.

James H Buszkiewicz, Jennifer F Bobb, Philip M Hurvitz, David Arterburn, Anne Vernez Moudon, Andrea Cook, Stephen J Mooney, Maricela Cruz, Shilpi Gupta, Paula Lozano and 4 more

Open access · greenAbstract read
In one paragraph

Article in International journal of obesity (2005), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
3.1field-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

14 citing papers in PubMed, 23 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

14 authors at 2 institutions in 1 country.

James H BuszkiewiczCenter for Public Health Nutrition, 305 Raitt Hall, #353410, University of Washington, Seattle, WA, USA. buszkiew@uw.edu.ORCID http://orcid.org/0000-0002-7919-7103
Jennifer F BobbKaiser Permanente Washington Health Research Institute, Seattle, WA, USA.
Philip M HurvitzUrban Form Lab, Department of Urban Design and Planning, College of Built Environments, University of Washington, Seattle, WA, USA.ORCID http://orcid.org/0000-0002-2944-0785
David ArterburnKaiser Permanente Washington Health Research Institute, Seattle, WA, USA.
Anne Vernez MoudonUrban Form Lab, Department of Urban Design and Planning, College of Built Environments, University of Washington, Seattle, WA, USA.ORCID http://orcid.org/0000-0001-8485-4799
Andrea CookKaiser Permanente Washington Health Research Institute, Seattle, WA, USA.
Stephen J MooneyDepartment of Epidemiology, School of Public Health, University of Washington, Seattle, WA, USA.
Maricela CruzKaiser Permanente Washington Health Research Institute, Seattle, WA, USA.
Shilpi GuptaCenter for Public Health Nutrition, 305 Raitt Hall, #353410, University of Washington, Seattle, WA, USA.
Paula LozanoKaiser Permanente Washington Health Research Institute, Seattle, WA, USA.
Dori E RosenbergKaiser Permanente Washington Health Research Institute, Seattle, WA, USA.
Mary Kay TheisKaiser Permanente Washington Health Research Institute, Seattle, WA, USA.
Jane AnauKaiser Permanente Washington Health Research Institute, Seattle, WA, USA.
Adam DrewnowskiCenter for Public Health Nutrition, 305 Raitt Hall, #353410, University of Washington, Seattle, WA, USA.
Kaiser Permanente Washington Health Research Institute · USUniversity of Washington · US

Funding

Scientific/Technical CoreP2CHD042828 · NICHD · UNIVERSITY OF WASHINGTON · PI SARA R. CURRAN · 2017 to 2026
$6.3M
Food Environment, Diet Quality and Disparities in ObesityR01DK076608 · NIDDK · UNIVERSITY OF WASHINGTON · PI DREWNOWSKI, ADAM · 2008 to 2019
$6.3M
Moving to Health: How changing built environments impact weight and glycemic controlR01DK114196 · NIDDK · KAISER FOUNDATION RESEARCH INSTITUTE · PI ARTERBURN, DAVID ERIC, DREWNOWSKI, ADAM · 2017 to 2021
$2.7M
The Automatic Context Measurement Tool: bringing environmental data to non-specialistsR00LM012868 · NLM · UNIVERSITY OF WASHINGTON · PI MOONEY, STEPHEN JOHN · 2019 to 2021
$687k
NICHD NIH HHS P2C HD042828NIDDK NIH HHS R01 DK076608NIDDK NIH HHS R01 DK114196NLM NIH HHS R00 LM012868
6 · The paper itself

Abstract

objectiveTo determine whether selected features of the built environment can predict weight gain in a large longitudinal cohort of adults.

methodsWeight trajectories over a 5-year period were obtained from electronic health records for 115,260 insured patients aged 18-64 years in the Kaiser Permanente Washington health care system. Home addresses were geocoded using ArcGIS. Built environment variables were population, residential unit, and road intersection densities captured using Euclidean-based SmartMaps at 800-m buffers. Counts of area supermarkets and fast food restaurants were obtained using network-based SmartMaps at 1600, and 5000-m buffers. Property values were a measure of socioeconomic status. Linear mixed effects models tested whether built environment variables at baseline were associated with long-term weight gain, adjusting for sex, age, race/ethnicity, Medicaid insurance, body weight, and residential property values.

resultsBuilt environment variables at baseline were associated with differences in baseline obesity prevalence and body mass index but had limited impact on weight trajectories. Mean weight gain for the full cohort was 0.06 kg at 1 year (95% CI: 0.03, 0.10); 0.64 kg at 3 years (95% CI: 0.59, 0.68), and 0.95 kg at 5 years (95% CI: 0.90, 1.00). In adjusted regression models, the top tertile of density metrics and frequency counts were associated with lower weight gain at 5-years follow-up compared to the bottom tertiles, though the mean differences in weight change for each follow-up year (1, 3, and 5) did not exceed 0.5 kg.

conclusionsBuilt environment variables that were associated with higher obesity prevalence at baseline had limited independent obesogenic power with respect to weight gain over time. Residential unit density had the strongest negative association with weight gain. Future work on the influence of built environment variables on health should also examine social context, including residential segregation and residential mobility.

Indexed as

Body-Weight TrajectoryAdolescentAdultBuilt EnvironmentFemaleHumansMaleMiddle AgedObesityRegression AnalysisUrban Population

Identifiers

PMID33976378
PMCPMC8592117
OpenAlexW3163053939

What OpenQuestion holds

Textmetadata
LicenceTDM
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.