Evidence map›Paper›PMID 35337829›Full record

ArticleEnvironmental research2022

Impact of land use and food environment on risk of type 2 diabetes: A national study of veterans, 2008-2018.

Sandra India-Aldana, Rania Kanchi, Samrachana Adhikari, Priscilla Lopez, Mark D Schwartz, Brian D Elbel, Pasquale E Rummo, Melissa A Meeker, Gina S Lovasi, Karen R Siegel and 2 more

Open access · hybridAbstract read
In one paragraph

Article in Environmental research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
2.0field-weighted citation impact, top 14% 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

6 citing papers in PubMed, 8 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

12 authors at 5 institutions in 1 country.

Sandra India-AldanaDivision of Epidemiology, Department of Population Health, NYU Grossman School of Medicine, 180 Madison Avenue, 5th Fl., New York, NY, 10016, USA.
Rania KanchiDivision of Epidemiology, Department of Population Health, NYU Grossman School of Medicine, 180 Madison Avenue, 5th Fl., New York, NY, 10016, USA.
Samrachana AdhikariDivision of Biostatistics, Department of Population Health, NYU Grossman School of Medicine, 180 Madison Avenue, 5th Fl., New York, NY, 10016, USA.
Priscilla LopezDivision of Epidemiology, Department of Population Health, NYU Grossman School of Medicine, 180 Madison Avenue, 5th Fl., New York, NY, 10016, USA.
Mark D SchwartzDivision of Comparative Effectiveness and Decision Science, Department of Population Health, NYU Grossman School of Medicine, 180 Madison Avenue, 9th Fl., New York, NY, 10016, USA; VA New York Harbor Healthcare System, 423 E 23rd, New York, NY, 10010, USA.
Brian D ElbelDivision of Health and Behavior, Section on Health Choice, Policy and Evaluation, Department of Population Health, NYU Grossman School of Medicine, 180 Madison Avenue, 3rd Fl., New York, NY, 10016, USA; NYU Wagner Graduate School of Public Service, 295 Lafayette Street, New York, NY, 10012, USA.
Pasquale E RummoDivision of Epidemiology, Department of Population Health, NYU Grossman School of Medicine, 180 Madison Avenue, 5th Fl., New York, NY, 10016, USA.
Melissa A MeekerDrexel University Dornsife School of Public Health, 3215 Market St, Philadelphia, PA 19104, USA.
Gina S LovasiDrexel University Dornsife School of Public Health, 3215 Market St, Philadelphia, PA 19104, USA.
Karen R SiegelDivision of Diabetes Translation, Centers for Disease Control and Prevention, Atlanta, GA, 30341, USA.
Yu ChenDivision of Epidemiology, Department of Population Health, NYU Grossman School of Medicine, 180 Madison Avenue, 5th Fl., New York, NY, 10016, USA; Department of Environmental Medicine, NYU Grossman School of Medicine, New York, NY, USA.
Lorna E ThorpeDivision of Epidemiology, Department of Population Health, NYU Grossman School of Medicine, 180 Madison Avenue, 5th Fl., New York, NY, 10016, USA. Electronic address: Lorna.Thorpe@nyulangone.org.
New York University · USDrexel University · USCenters for Disease Control and Prevention · USVA NY Harbor Healthcare System · USWagner College · US

Funding

Component A: Impact of Community Factors on Geographic Disparities in Diabetes and Obesity NationwideU01DP006299 · DP · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI THORPE, LORNA · 2017 to 2021
$4.1M
Component A: A multi-level study of community context and type 2 diabetes and coronary heart disease using electronic health record and new primary data across nested geographies in PennsylvaniaU01DP006296 · DP · GEISINGER CLINIC · PI HIRSCH, ANNEMARIE GREGORY · 2017 to 2021
$3.8M
Prioritizing county-level social determinants that contribute to the greater burden of diabetes and hypertension in the USU01DP006302 · DP · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI CARSON, APRIL P · 2017 to 2021
$3.6M
Component B: Coordinating Center for Community Characteristics Associated with Geographic Disparities in DiabetesU01DP006293 · DP · DREXEL UNIVERSITY · PI MCCLURE, LESLIE AIN · 2017 to 2021
$3.1M
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
ACL HHS U01DP006293ACL HHS U01DP006296ACL HHS U01DP006299ACL HHS U01DP006302NCCDPHP CDC HHS U01 DP006293NCCDPHP CDC HHS U01 DP006296NCCDPHP CDC HHS U01 DP006299NCCDPHP CDC HHS U01 DP006302NIA NIH HHS R01 AG049970NIA NIH HHS R56 AG049970
6 · The paper itself

Abstract

backgroundLarge-scale longitudinal studies evaluating influences of the built environment on risk for type 2 diabetes (T2D) are scarce, and findings have been inconsistent.

objectiveTo evaluate whether land use environment (LUE), a proxy of neighborhood walkability, is associated with T2D risk across different US community types, and to assess whether the association is modified by food environment.

methodsThe Veteran's Administration Diabetes Risk (VADR) study is a retrospective cohort of diabetes-free US veteran patients enrolled in VA primary care facilities nationwide from January 1, 2008, to December 31, 2016, and followed longitudinally through December 31, 2018. A total of 4,096,629 patients had baseline addresses available in electronic health records that were geocoded and assigned a census tract-level LUE score. LUE scores were divided into quartiles, where a higher score indicated higher neighborhood walkability levels. New diagnoses for T2D were identified using a published computable phenotype. Adjusted time-to-event analyses using piecewise exponential models were fit within four strata of community types (higher-density urban, lower-density urban, suburban/small town, and rural). We also evaluated effect modification by tract-level food environment measures within each stratum.

resultsIn adjusted analyses, higher LUE had a protective effect on T2D risk in rural and suburban/small town communities (linear quartile trend test p-value <0.001). However, in lower density urban communities, higher LUE increased T2D risk (linear quartile trend test p-value <0.001) and no association was found in higher density urban communities (linear quartile trend test p-value = 0.317). Particularly strong protective effects were observed for veterans living in suburban/small towns with more supermarkets and more walkable spaces (p-interaction = 0.001).

conclusionAmong veterans, LUE may influence T2D risk, particularly in rural and suburban communities. Food environment may modify the association between LUE and T2D.

Indexed as

Diabetes Mellitus, Type 2VeteransHumansResidence CharacteristicsRetrospective StudiesWalkingFood environmentLand use environmentType 2 diabetesVeterans

Identifiers

PMID35337829
PMCPMC10424702
OpenAlexW4221024050

What Socratic 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 Socratic graph.