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Environmental data and methods from the Accumulating Data to Optimally Predict Obesity Treatment (ADOPT) core measures environmental working group

This article describes geospatial datasets and exemplary data across five environmental domains (walkability, socioeconomic deprivation, urbanicity, personal safety, and food outlet accessibility). The environmental domain is one of four domains (behavioral, biological, environmental and psychosocia...

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Autores principales: Slotman, Beth A., Stinchcomb, David G., Powell-Wiley, Tiffany M., Ostendorf, Danielle M., Saelens, Brian E., Gorin, Amy A., Zenk, Shannon N., Berrigan, David
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8920874/
https://www.ncbi.nlm.nih.gov/pubmed/35300389
http://dx.doi.org/10.1016/j.dib.2022.108002
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author Slotman, Beth A.
Stinchcomb, David G.
Powell-Wiley, Tiffany M.
Ostendorf, Danielle M.
Saelens, Brian E.
Gorin, Amy A.
Zenk, Shannon N.
Berrigan, David
author_facet Slotman, Beth A.
Stinchcomb, David G.
Powell-Wiley, Tiffany M.
Ostendorf, Danielle M.
Saelens, Brian E.
Gorin, Amy A.
Zenk, Shannon N.
Berrigan, David
author_sort Slotman, Beth A.
collection PubMed
description This article describes geospatial datasets and exemplary data across five environmental domains (walkability, socioeconomic deprivation, urbanicity, personal safety, and food outlet accessibility). The environmental domain is one of four domains (behavioral, biological, environmental and psychosocial) in which the Accumulating Data to Optimally Predict obesity Treatment (ADOPT) Core Measures Project suggested measures to help explain variation in responses to weight loss interventions. These data are intended to facilitate additional research on potential environmental moderators of responses to weight loss, physical activity, or diet related interventions. These data represent a mix of publicly and commercially available pre-existing data that were downloaded, cleaned, restructured and analyzed to create datasets at the United States (U.S.) block group and/or census tract level for the five domains. Additionally, the resource includes detailed methods for obtaining, cleaning and summarizing two datasets concerning safety and the food environment that are only available commercially. Across the five domains considered, we include component as well as derived variables for three of the five domains. There are two versions of the National Walkability Index Dataset (one based on 2013 data and one on 2019 data) consisting of 15 variables. The Neighborhood Deprivation Index dataset contains 18 variables and is based on the US Census Bureau's 5-year American Community Survey (ACS) data for 2013–2017. The urbanicity dataset contains 11 variables and is based on USDA rural-urban commuting (RUCA) codes and Census Bureau urban/rural population data from 2010. Personal safety and food outlet accessibility data were purchased through commercial vendors and are not in the public domain. Thus, only exemplary figures and detailed instructions are provided. The website housing these datasets and examples should serve as a valuable resource for researchers who wish to examine potential environmental moderators of responses to weight loss and related interventions in the U.S.
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spelling pubmed-89208742022-03-16 Environmental data and methods from the Accumulating Data to Optimally Predict Obesity Treatment (ADOPT) core measures environmental working group Slotman, Beth A. Stinchcomb, David G. Powell-Wiley, Tiffany M. Ostendorf, Danielle M. Saelens, Brian E. Gorin, Amy A. Zenk, Shannon N. Berrigan, David Data Brief Data Article This article describes geospatial datasets and exemplary data across five environmental domains (walkability, socioeconomic deprivation, urbanicity, personal safety, and food outlet accessibility). The environmental domain is one of four domains (behavioral, biological, environmental and psychosocial) in which the Accumulating Data to Optimally Predict obesity Treatment (ADOPT) Core Measures Project suggested measures to help explain variation in responses to weight loss interventions. These data are intended to facilitate additional research on potential environmental moderators of responses to weight loss, physical activity, or diet related interventions. These data represent a mix of publicly and commercially available pre-existing data that were downloaded, cleaned, restructured and analyzed to create datasets at the United States (U.S.) block group and/or census tract level for the five domains. Additionally, the resource includes detailed methods for obtaining, cleaning and summarizing two datasets concerning safety and the food environment that are only available commercially. Across the five domains considered, we include component as well as derived variables for three of the five domains. There are two versions of the National Walkability Index Dataset (one based on 2013 data and one on 2019 data) consisting of 15 variables. The Neighborhood Deprivation Index dataset contains 18 variables and is based on the US Census Bureau's 5-year American Community Survey (ACS) data for 2013–2017. The urbanicity dataset contains 11 variables and is based on USDA rural-urban commuting (RUCA) codes and Census Bureau urban/rural population data from 2010. Personal safety and food outlet accessibility data were purchased through commercial vendors and are not in the public domain. Thus, only exemplary figures and detailed instructions are provided. The website housing these datasets and examples should serve as a valuable resource for researchers who wish to examine potential environmental moderators of responses to weight loss and related interventions in the U.S. Elsevier 2022-03-02 /pmc/articles/PMC8920874/ /pubmed/35300389 http://dx.doi.org/10.1016/j.dib.2022.108002 Text en https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Data Article
Slotman, Beth A.
Stinchcomb, David G.
Powell-Wiley, Tiffany M.
Ostendorf, Danielle M.
Saelens, Brian E.
Gorin, Amy A.
Zenk, Shannon N.
Berrigan, David
Environmental data and methods from the Accumulating Data to Optimally Predict Obesity Treatment (ADOPT) core measures environmental working group
title Environmental data and methods from the Accumulating Data to Optimally Predict Obesity Treatment (ADOPT) core measures environmental working group
title_full Environmental data and methods from the Accumulating Data to Optimally Predict Obesity Treatment (ADOPT) core measures environmental working group
title_fullStr Environmental data and methods from the Accumulating Data to Optimally Predict Obesity Treatment (ADOPT) core measures environmental working group
title_full_unstemmed Environmental data and methods from the Accumulating Data to Optimally Predict Obesity Treatment (ADOPT) core measures environmental working group
title_short Environmental data and methods from the Accumulating Data to Optimally Predict Obesity Treatment (ADOPT) core measures environmental working group
title_sort environmental data and methods from the accumulating data to optimally predict obesity treatment (adopt) core measures environmental working group
topic Data Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8920874/
https://www.ncbi.nlm.nih.gov/pubmed/35300389
http://dx.doi.org/10.1016/j.dib.2022.108002
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