Who and Where: A Socio-Spatial Integrated Approach for Community-Based Health Research

Social and spatial characteristics of a population often interact to influence health outcomes, suggesting a need to jointly analyze both to offer useful insights in community health. However, researchers have used either social or spatial analyses to examine community-based health issues and inform...

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Main Authors: Jeanne-Marie R. Stacciarini, Raffaele Vacca, Liang Mao
Format: Article
Language:English
Published: MDPI AG 2018-06-01
Series:International Journal of Environmental Research and Public Health
Subjects:
Online Access:http://www.mdpi.com/1660-4601/15/7/1375
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spelling doaj-1ec625f3277a45059e8abdbaac8a865c2020-11-24T21:39:12ZengMDPI AGInternational Journal of Environmental Research and Public Health1660-46012018-06-01157137510.3390/ijerph15071375ijerph15071375Who and Where: A Socio-Spatial Integrated Approach for Community-Based Health ResearchJeanne-Marie R. Stacciarini0Raffaele Vacca1Liang Mao2College of Nursing, University of Florida, Gainesville, FL 32610, USADepartment of Sociology and Criminology & Law, University of Florida, Gainesville, FL 32611, USADepartment of Geography, University of Florida, Gainesville, FL 32611, USASocial and spatial characteristics of a population often interact to influence health outcomes, suggesting a need to jointly analyze both to offer useful insights in community health. However, researchers have used either social or spatial analyses to examine community-based health issues and inform intervention programs. We propose a combined socio-spatial analytic approach to develop a social network with spatial weights and a spatial statistic with social weights, and apply them to an ongoing study of mental and physical well-being of rural Latino immigrants in North Florida, USA. We demonstrate how this approach can be used to calculate measures, such as social network centrality, support contact dyads, and spatial kernel density based on a health survey data. Findings reveal that the integrated approach accurately reflected interactions between social and spatial elements, and identified community members (who) and locations (where) that should be prioritized for community-based health interventions.http://www.mdpi.com/1660-4601/15/7/1375community healthrural Latino immigrantsmental well-beingnetwork analysisspatial statisticsintervention
collection DOAJ
language English
format Article
sources DOAJ
author Jeanne-Marie R. Stacciarini
Raffaele Vacca
Liang Mao
spellingShingle Jeanne-Marie R. Stacciarini
Raffaele Vacca
Liang Mao
Who and Where: A Socio-Spatial Integrated Approach for Community-Based Health Research
International Journal of Environmental Research and Public Health
community health
rural Latino immigrants
mental well-being
network analysis
spatial statistics
intervention
author_facet Jeanne-Marie R. Stacciarini
Raffaele Vacca
Liang Mao
author_sort Jeanne-Marie R. Stacciarini
title Who and Where: A Socio-Spatial Integrated Approach for Community-Based Health Research
title_short Who and Where: A Socio-Spatial Integrated Approach for Community-Based Health Research
title_full Who and Where: A Socio-Spatial Integrated Approach for Community-Based Health Research
title_fullStr Who and Where: A Socio-Spatial Integrated Approach for Community-Based Health Research
title_full_unstemmed Who and Where: A Socio-Spatial Integrated Approach for Community-Based Health Research
title_sort who and where: a socio-spatial integrated approach for community-based health research
publisher MDPI AG
series International Journal of Environmental Research and Public Health
issn 1660-4601
publishDate 2018-06-01
description Social and spatial characteristics of a population often interact to influence health outcomes, suggesting a need to jointly analyze both to offer useful insights in community health. However, researchers have used either social or spatial analyses to examine community-based health issues and inform intervention programs. We propose a combined socio-spatial analytic approach to develop a social network with spatial weights and a spatial statistic with social weights, and apply them to an ongoing study of mental and physical well-being of rural Latino immigrants in North Florida, USA. We demonstrate how this approach can be used to calculate measures, such as social network centrality, support contact dyads, and spatial kernel density based on a health survey data. Findings reveal that the integrated approach accurately reflected interactions between social and spatial elements, and identified community members (who) and locations (where) that should be prioritized for community-based health interventions.
topic community health
rural Latino immigrants
mental well-being
network analysis
spatial statistics
intervention
url http://www.mdpi.com/1660-4601/15/7/1375
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