Evidence map›Paper›PMID 38929017›Full record

ArticleInternational journal of environmental research and public health2024

Disaggregation of Green Space Access, Walkability, and Behavioral Risk Factor Data for Precise Estimation of Local Population Characteristics.

Saurav Guha, Michael Alonzo, Pierre Goovaerts, LuAnn L Brink, Meghana Ray, Todd Bear, Saumyadipta Pyne

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Saurav GuhaHealth Analytics Network, Pittsburgh, PA 15237, USA.
Michael AlonzoDepartment of Environmental Science, American University, Washington, DC 20016, USA.ORCID 0000-0001-9409-2740
Pierre GoovaertsBiomedware, Inc., Ann Arbor, MI 48103, USA.
LuAnn L BrinkAllegheny County Health Department, Pittsburgh, PA 15219, USA.
Meghana RayHealth Analytics Network, Pittsburgh, PA 15237, USA.ORCID 0000-0001-9054-1844
Todd BearDepartment of Family Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15260, USA.ORCID 0000-0001-5252-6926
Saumyadipta PyneHealth Analytics Network, Pittsburgh, PA 15237, USA.

Funding

Geostatistical Software for Non-Parametric Geostatistical Modeling of UncertaintyR44LM014519 · NLM · BIOMEDWARE · PI GOOVAERTS, PIERRE E · 2024 to 2025
$2.0M
Geostatistical software for merging multivariate data with various spatial supportsR44ES031875 · NIEHS · BIOMEDWARE · PI GOOVAERTS, PIERRE E · 2021 to 2022
$1.7M
NIEHS NIH HHS R44 ES031875NLM NIH HHS R44 LM014519
6 · The paper itself

Abstract

backgroundSocial and Environmental Determinants of Health (SEDH) provide us with a conceptual framework to gain insights into possible associations among different human behaviors and the corresponding health outcomes that take place often in and around complex built environments. Developing better built environments requires an understanding of those aspects of a community that are most likely to have a measurable impact on the target SEDH. Yet data on local characteristics at suitable spatial scales are often unavailable. We aim to address this issue by application of different data disaggregation methods.

methodsWe applied different approaches to data disaggregation to obtain small area estimates of key behavioral risk factors, as well as geospatial measures of green space access and walkability for each zip code of Allegheny County in southwestern Pennsylvania.

resultsTables and maps of local characteristics revealed their overall spatial distribution along with disparities therein across the county. While the top ranked zip codes by behavioral estimates generally have higher than the county's median individual income, this does not lead them to have higher than its median green space access or walkability.

conclusionWe demonstrated the utility of data disaggregation for addressing complex questions involving community-specific behavioral attributes and built environments with precision and rigor, which is especially useful for a diverse population. Thus, different types of data, when comparable at a common local scale, can provide key integrative insights for researchers and policymakers.

Indexed as

Residence CharacteristicsWalkingBuilt EnvironmentEnvironment DesignHealth BehaviorHumansParks, RecreationalPennsylvaniaRisk FactorsAllegheny Countybuilt environmentGISkrigingsmall area estimationzip code

Identifiers

PMID38929017
PMCPMC11203488

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LicenceCC BY
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Registered trials

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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.