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EM: Neighborhood greenness and chronic health conditions in Medicare beneficiaries, Miami-Dade County, Florida, USA (EM-876)
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EM Identity and Description
EM Identification
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EM ID
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EM-876 |
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EM Short Name
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Neighborhood greenness and health, FL, USA |
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EM Full Name
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Neighborhood greenness and chronic health conditions in Medicare beneficiaries, Miami-Dade County, Florida, USA |
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EM Source or Collection
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None |
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EM Source Document ID
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417 |
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Document Author
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Brown, S. C., J. Lombard, K. Wang, M. M. Byrne, M. Toro, E. Plater-Zyberk, D. J. Feaster, J. Kardys, M. I. Nardi, G. Perez-Gomez, H. M. Pantin, and J. Szapocznik |
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Document Year
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2016 |
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Document Title
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Neighborhood greenness and chronic health conditions in Medicare beneficiaries |
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Document Status
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Peer reviewed and published |
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Comments on Status
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Published journal manuscript |
Software and Access
| Not applicable | |
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Contact Name
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Scott C. Brown |
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Contact Address
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Department of Public Health Sciences, University of Miami Miller School of Medicine, 1120 NW 14th Street, Clinical Research Building (CRB), Room 1065, Miami FL 33136 |
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Contact Email
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sbrown@med.miami.edu |
EM Description
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Summary Description
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ABSTRACT: "Introduction: Prior studies suggest that exposure to the natural environment may impact health. The present study examines the association between objective measures of block-level greenness (vegetative presence) and chronic medical conditions, including cardiometabolic conditions, in a large population-based sample of Medicare beneficiaries in Miami-Dade County, Florida. Methods: The sample included 249,405 Medicare beneficiaries aged >=65 years whose location (ZIP+4) within Miami-Dade County, Florida, did not change, from 2010 to 2011. Data were obtained in 2013 and multilevel analyses conducted in 2014 to examine relationships between greenness, measured by mean Normalized Difference Vegetation Index from satellite imagery at the Census block level, and chronic health conditions in 2011, adjusting for neighborhood median household income, individual age, gender, race, and ethnicity. Results: Higher greenness was significantly associated with better health, adjusting for covariates: An increase in mean block-level Normalized Difference Vegetation Index from 1 SD less to 1 SD more than the mean was associated with 49 fewer chronic conditions per 1,000 individuals, which is approximately similar to a reduction in age of the overall study population by 3 years. This same level of increase in mean Normalized Difference Vegetation Index was associated with a reduced risk of diabetes by 14%, hypertension by 13%, and hyperlipidemia by 10%. Planned post-hoc analyses revealed stronger and more consistently positive relationships between greenness and health in lower- than higher-income neighborhoods. Conclusions: Greenness or vegetative presence may be effective in promoting health in older populations, particularly in poor neighborhoods, possibly due to increased time outdoors, physical activity, or stress mitigation." |
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Specific Policy or Decision Context Cited
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None identified |
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Biophysical Context
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No additional description provided |
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EM Scenario Drivers
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No scenarios presented |
EM Relationship to Other EMs or Applications
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Method Only, Application of Method or Model Run
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Method + Application |
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New or Pre-existing EM?
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New or revised model |
Related EMs (for example, other versions or derivations of this EM) described in ESML
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Document ID for related EM
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None |
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EM ID for related EM
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None |
EM Modeling Approach
EM Relationship to Time
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EM Temporal Extent
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2010-2011 |
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EM Time Dependence
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time-stationary |
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EM Time Reference (Future/Past)
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Not applicable |
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EM Time Continuity
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Not applicable |
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EM Temporal Grain Size Value
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Not applicable |
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EM Temporal Grain Size Unit
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Not applicable |
EM Spatial Extent
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Bounding Type
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Geopolitical |
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Spatial Extent Name
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Miami-Dade County |
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Spatial Extent Area (Magnitude)
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1000-10,000 km^2. |
Spatial Distribution of Computations
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EM Spatial Distribution
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spatially distributed (in at least some cases) |
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Spatial Grain Type
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other (specify), for irregular (e.g., stream reach, lake basin) |
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Spatial Grain Size
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Census block |
EM Structure and Computation Approach
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EM Computational Approach
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Analytic |
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EM Determinism
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deterministic |
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Statistical Estimation of EM
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Model Checking Procedures Used
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Model Calibration Reported?
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Not applicable |
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Model Goodness of Fit Reported?
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No |
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Goodness of Fit (metric| value | unit)
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None |
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Model Operational Validation Reported?
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No |
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Model Uncertainty Analysis Reported?
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No |
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Model Sensitivity Analysis Reported?
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No |
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Model Sensitivity Analysis Include Interactions?
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Not applicable |
EM Locations, Environments, Ecology
Location of EM Application
Terrestrial location (Classification hierarchy: Continent > Country > U.S. State [United States only])
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Marine location (Classification hierarchy: Realm > Region > Province > Ecoregion)
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| None |
Centroid Lat/Long (Decimal Degree)
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Centroid Latitude
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25.64 |
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Centroid Longitude
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-80.5 |
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Centroid Datum
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WGS84 |
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Centroid Coordinates Status
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Estimated |
Environments and Scales Modeled
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EM Environmental Sub-Class
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Created Greenspace |
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Specific Environment Type
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urban neighborhood greenspace |
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EM Ecological Scale
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Ecological scale is coarser than that of the Environmental Sub-class |
Scale and taxa of organisms modeled
Scale of differentiation of organisms modeled
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EM Organismal Scale
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Not applicable |
Taxonomic level and name of organisms or groups identified
taxonomyHelp
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| None Available |
EnviroAtlas URL
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| Percent Population other than White, Non-Hispanic, Percent Population under 13 Years Old |
EM Ecosystem Goods and Services (EGS) potentially modeled, by classification system
CICES v 4.3 - Common International Classification of Ecosystem Services (Section > Division > Group > Class)
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(Environmental Subclass > Ecological End-Product (EEP) > EEP Subclass > EEP Modifier)
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EM Variable Names (and Units)
Predictor
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Intermediate
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Intermediate (Computed) Variables (and Units)
view details (4 variables)
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Response
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