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Neighborhood AND spatial modeling

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https://www.readbyqxmd.com/read/28445425/association-of-long-term-near-highway-exposure-to-ultrafine-particles-with-cardiovascular-diseases-diabetes-and-hypertension
#1
Yu Li, Kevin J Lane, Laura Corlin, Allison P Patton, John L Durant, Mohan Thanikachalam, Mark Woodin, Molin Wang, Doug Brugge
Ultrafine particle (UFP) concentrations are elevated near busy roadways, however, their effects on prevalence of cardiovascular diseases, diabetes, and hypertension are not well understood. To investigate these associations, data on demographics, diseases, medication use, and time of activities were collected by in-home surveys for 704 participants in three pairs of near-highway and urban background neighborhoods in and near Boston (MA, USA). Body mass index (BMI) was measured for a subset of 435 participants...
April 26, 2017: International Journal of Environmental Research and Public Health
https://www.readbyqxmd.com/read/28404541/making-air-pollution-visible-a-tool-for-promoting-environmental-health-literacy
#2
Ekaterina Galkina Cleary, Allison P Patton, Hsin-Ching Wu, Alan Xie, Joseph Stubblefield, William Mass, Georges Grinstein, Susan Koch-Weser, Doug Brugge, Carolyn Wong
BACKGROUND: Digital maps are instrumental in conveying information about environmental hazards geographically. For laypersons, computer-based maps can serve as tools to promote environmental health literacy about invisible traffic-related air pollution and ultrafine particles. Concentrations of these pollutants are higher near major roadways and increasingly linked to adverse health effects. Interactive computer maps provide visualizations that can allow users to build mental models of the spatial distribution of ultrafine particles in a community and learn about the risk of exposure in a geographic context...
April 12, 2017: JMIR Public Health and Surveillance
https://www.readbyqxmd.com/read/28385056/spatial-social-polarization-and-birth-outcomes-preterm-birth-and-infant-mortality-new-york-city-2010-14
#3
M Huynh, J Spasojevic, W Li, G Maduro, G Van Wye, P D Waterman, N Krieger
AIMS: This study assessed the relationship between spatial social polarization measured by the index of the concentration of the extremes (ICE) and preterm birth (PTB) and infant mortality (IM) in New York City. A secondary aim was to examine the ICE measure in comparison to neighborhood poverty. METHODS: The sample included singleton births to adult women in New York City, 2010-2014 ( n=532,806). Three ICE measures were employed at the census tract level: ICE - Income (persons in households in the bottom vs top 20th percentile of US annual household income), ICE -Race/Ethnicity (black non-Hispanic vs white non-Hispanic populations), and ICE - Income + Race/Ethnicity combined...
April 1, 2017: Scandinavian Journal of Public Health
https://www.readbyqxmd.com/read/28380130/spatial-temporal-diffusion-of-dengue-in-the-municipality-of-rio-de-janeiro-brazil-2000-2013
#4
Diego Ricardo Xavier, Mônica de Avelar Figueiredo Mafra Magalhães, Renata Gracie, Izabel Cristina Dos Reis, Vanderlei Pascoal de Matos, Christovam Barcellos
The city of Rio de Janeiro, Brazil, shows high potential receptiveness to the introduction, dissemination, and persistence of dengue transmission. The pattern of territorial occupation in the municipality produced a heterogeneous and diverse mosaic, with differential vector distribution between and within neighborhoods, producing distinct epidemics on this scale of observation. The study seeks to identify these epidemics and the pattern of spatial and temporal diffusion of dengue transmission. A model was used for the identification of epidemics, considering the epidemic peak years and months, spatial distribution, and permanence of epidemics from January 2000 to December 2013...
March 30, 2017: Cadernos de Saúde Pública
https://www.readbyqxmd.com/read/28369149/socioeconomic-and-environmental-determinants-of-dengue-transmission-in-an-urban-setting-an-ecological-study-in-noum%C3%A3-a-new-caledonia
#5
Raphaël M Zellweger, Jorge Cano, Morgan Mangeas, François Taglioni, Alizé Mercier, Marc Despinoy, Christophe E Menkès, Myrielle Dupont-Rouzeyrol, Birgit Nikolay, Magali Teurlai
BACKGROUND: Dengue is a mosquito-borne virus that causes extensive morbidity and economic loss in many tropical and subtropical regions of the world. Often present in cities, dengue virus is rapidly spreading due to urbanization, climate change and increased human movements. Dengue cases are often heterogeneously distributed throughout cities, suggesting that small-scale determinants influence dengue urban transmission. A better understanding of these determinants is crucial to efficiently target prevention measures such as vector control and education...
April 2017: PLoS Neglected Tropical Diseases
https://www.readbyqxmd.com/read/28362024/modeling-a-secular-trend-by-monte-carlo-simulation-of-height-biased-migration-in-a-spatial-network
#6
Detlef Groth
Background: In a recent Monte Carlo simulation, the clustering of body height of Swiss military conscripts within a spatial network with characteristic features of the natural Swiss geography was investigated. In this study I examined the effect of migration of tall individuals into network hubs on the dynamics of body height within the whole spatial network. The aim of this study was to simulate height trends. Material and methods: Three networks were used for modeling, a regular rectangular fishing net like network, a real world example based on the geographic map of Switzerland, and a random network...
February 23, 2017: Anthropologischer Anzeiger; Bericht über die Biologisch-anthropologische Literatur
https://www.readbyqxmd.com/read/28358862/comprehensive-framework-for-visualizing-and-analyzing-spatio-temporal-dynamics-of-racial-diversity-in-the-entire-united-states
#7
Anna Dmowska, Tomasz F Stepinski, Pawel Netzel
The United States is increasingly becoming a multi-racial society. To understand multiple consequences of this overall trend to our neighborhoods we need a methodology capable of spatio-temporal analysis of racial diversity at the local level but also across the entire U.S. Furthermore, such methodology should be accessible to stakeholders ranging from analysts to decision makers. In this paper we present a comprehensive framework for visualizing and analyzing diversity data that fulfills such requirements...
2017: PloS One
https://www.readbyqxmd.com/read/28346484/a-neighborhood-wide-association-study-nwas-example-of-prostate-cancer-aggressiveness
#8
Shannon M Lynch, Nandita Mitra, Michelle Ross, Craig Newcomb, Karl Dailey, Tara Jackson, Charnita M Zeigler-Johnson, Harold Riethman, Charles C Branas, Timothy R Rebbeck
PURPOSE: Cancer results from complex interactions of multiple variables at the biologic, individual, and social levels. Compared to other levels, social effects that occur geospatially in neighborhoods are not as well-studied, and empiric methods to assess these effects are limited. We propose a novel Neighborhood-Wide Association Study(NWAS), analogous to genome-wide association studies(GWAS), that utilizes high-dimensional computing approaches from biology to comprehensively and empirically identify neighborhood factors associated with disease...
2017: PloS One
https://www.readbyqxmd.com/read/28333630/multilinear-spatial-discriminant-analysis-for-dimensionality-reduction
#9
Sen Yuan, Xia Mao, Lijiang Chen
In the last few years, great efforts have been made to extend the linear projection technique (LPT) for multidimensional data (i.e., tensor), generally referred to as the multilinear projection technique (MPT). The vectorized nature of LPT requires high-dimensional data to be converted into vector, and hence may lose spatial neighborhood information of raw data. MPT well addresses this problem by encoding multidimensional data as general tensors of a second or even higher order. In this paper, we propose a novel multilinear projection technique, called multilinear spatial discriminant analysis (MSDA), to identify the underlying manifold of high-order tensor data...
June 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
https://www.readbyqxmd.com/read/28328502/spatial-statistics-for-segmenting-histological-structures-in-h-e-stained-tissue-images
#10
Luong Nguyen, A Burak Tosun, Jeffrey Fine, Adrian Lee, D Lansing Taylor, Chakra Chennubhotla
Segmenting a broad class of histological structures in transmitted light and/or fluorescence-based images is a prerequisite for determining the pathological basis of cancer, elucidating spatial interactions between histological structures in tumor microenvironments (e.g. tumor infiltrating lymphocytes), facilitating precision medicine studies with deep molecular profiling, and providing an exploratory tool for pathologists. Our paper focuses on segmenting histological structures in hematoxylin and eosin (H&E) stained images of breast tissues, e...
March 16, 2017: IEEE Transactions on Medical Imaging
https://www.readbyqxmd.com/read/28317230/cortical-surface-based-threshold-free-cluster-enhancement-and-cortexwise-mediation
#11
Tristram A Lett, Lea Waller, Heike Tost, Ilya M Veer, Arash Nazeri, Susanne Erk, Eva J Brandl, Katrin Charlet, Anne Beck, Sabine Vollstädt-Klein, Anne Jorde, Falk Kiefer, Andreas Heinz, Andreas Meyer-Lindenberg, M Mallar Chakravarty, Henrik Walter
Threshold-free cluster enhancement (TFCE) is a sensitive means to incorporate spatial neighborhood information in neuroimaging studies without using arbitrary thresholds. The majority of methods have applied TFCE to voxelwise data. The need to understand the relationship among multiple variables and imaging modalities has become critical. We propose a new method of applying TFCE to vertexwise statistical images as well as cortexwise (either voxel- or vertexwise) mediation analysis. Here we present TFCE_mediation, a toolbox that can be used for cortexwise multiple regression analysis with TFCE, and additionally cortexwise mediation using TFCE...
March 20, 2017: Human Brain Mapping
https://www.readbyqxmd.com/read/28294963/voxel-based-neighborhood-for-spatial-shape-pattern-classification-of-lidar-point-clouds-with-supervised-learning
#12
Victoria Plaza-Leiva, Jose Antonio Gomez-Ruiz, Anthony Mandow, Alfonso García-Cerezo
Improving the effectiveness of spatial shape features classification from 3D lidar data is very relevant because it is largely used as a fundamental step towards higher level scene understanding challenges of autonomous vehicles and terrestrial robots. In this sense, computing neighborhood for points in dense scans becomes a costly process for both training and classification. This paper proposes a new general framework for implementing and comparing different supervised learning classifiers with a simple voxel-based neighborhood computation where points in each non-overlapping voxel in a regular grid are assigned to the same class by considering features within a support region defined by the voxel itself...
March 15, 2017: Sensors
https://www.readbyqxmd.com/read/28236183/validation-of-a-google-street-view-based-neighborhood-disorder-observational-scale
#13
Miriam Marco, Enrique Gracia, Manuel Martín-Fernández, Antonio López-Quílez
Recently, there has been a growing interest in developing new tools to measure neighborhood features using the benefits of emerging technologies. This study aimed to assess the psychometric properties of a neighborhood disorder observational scale using Google Street View (GSV). Two groups of raters conducted virtual audits of neighborhood disorder on all census block groups (N = 92) in a district of the city of Valencia (Spain). Four different analyses were conducted to validate the instrument. First, inter-rater reliability was assessed through intraclass correlation coefficients, indicating moderated levels of agreement among raters...
April 2017: Journal of Urban Health: Bulletin of the New York Academy of Medicine
https://www.readbyqxmd.com/read/28225909/tuberculosis-as-a-marker-of-inequities-in-the-context-of-socio-spatial-transformation
#14
Alexandre San Pedro, Gerusa Gibson, Jefferson Pereira Caldas Dos Santos, Luciano Medeiros de Toledo, Paulo Chagastelles Sabroza, Rosely Magalhães de Oliveira
OBJECTIVE: This study aims to analyze the association between the incidence of tuberculosis and different socioeconomic indicators in a territory of intense transformation of the urban space. METHODS: This is an ecological study, whose analysis units were the neighborhoods of the city of Itaboraí, state of Rio de Janeiro, Brazil. The data have been analyzed by generalized linear models. The response variable was incidence of tuberculosis from 2006 to 2011. The independent variables were the socio-demographic indicators...
February 16, 2017: Revista de Saúde Pública
https://www.readbyqxmd.com/read/28208207/-spatial-distribution-of-type-2-diabetes-mellitus-in-berlin-application-of-a-geographically-weighted-regression-analysis-to-identify-location-specific-risk-groups
#15
Boris Kauhl, Jonas Pieper, Jürgen Schweikart, Andrea Keste, Marita Moskwyn
Understanding which population groups in which locations are at higher risk for type 2 diabetes mellitus (T2DM) allows efficient and cost-effective interventions targeting these risk-populations in great need in specific locations. The goal of this study was to analyze the spatial distribution of T2DM and to identify the location-specific, population-based risk factors using global and local spatial regression models. To display the spatial heterogeneity of T2DM, bivariate kernel density estimation was applied...
February 16, 2017: Das Gesundheitswesen
https://www.readbyqxmd.com/read/28160971/inter-relationships-between-objective-and-subjective-measures-of-the-residential-environment-among-urban-african-american-women
#16
Shawnita Sealy-Jefferson, Lynne Messer, Jaime Slaughter-Acey, Dawn P Misra
PURPOSE: The inter-relationships between objective (census based) and subjective (resident reported) measures of the residential environment is understudied in African American (AA) populations. METHODS: Using data from the Life Influences on Fetal Environments Study (2009-2011; n = 1387) of AA women, we quantified the area-level variation in subjective reports of residential healthy food availability, walkability, safety, and disorder that can be accounted for with an objective neighborhood disadvantage index (NDI)...
March 2017: Annals of Epidemiology
https://www.readbyqxmd.com/read/28155876/failure-and-recovery-in-dynamical-networks
#17
L Böttcher, M Luković, J Nagler, S Havlin, H J Herrmann
Failure, damage spread and recovery crucially underlie many spatially embedded networked systems ranging from transportation structures to the human body. Here we study the interplay between spontaneous damage, induced failure and recovery in both embedded and non-embedded networks. In our model the network's components follow three realistic processes that capture these features: (i) spontaneous failure of a component independent of the neighborhood (internal failure), (ii) failure induced by failed neighboring nodes (external failure) and (iii) spontaneous recovery of a component...
February 3, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28145983/statistical-methods-to-study-variation-in-associations-between-food-store-availability-and-body-mass-in-the-multi-ethnic-study-of-atherosclerosis
#18
Jonggyu Baek, Jana A Hirsch, Kari Moore, Loni Philip Tabb, Tonatiuh Barrientos-Gutierrez, Lynda D Lisabeth, Ana V Diez-Roux, Brisa N Sánchez
Research linking characteristics of the neighborhood environment to health has relied on traditional regression methods where prespecified distances from participant's locations or areas are used to operationalize neighborhood-level measures. Because the relevant spatial scale of neighborhood environment measures may differ across places or individuals, using prespecified distances could result in biased association estimates or efficiency losses. We use novel hierarchical distributed lag models and data from the Multi-Ethnic Study of Atherosclerosis (MESA) to (1) examine whether and how the association between the availability of favorable food stores and body mass index (BMI) depends on continuous distance from participant locations (instead of traditional buffers), thus allowing us to indirectly infer the spatial scale at which this association operates; (2) examine if the spatial scale and magnitude of the association differs across six MESA sites, and (3) across individuals...
May 2017: Epidemiology
https://www.readbyqxmd.com/read/28137675/relative-risk-for-hiv-in-india-an-estimate-using-conditional-auto-regressive-models-with-bayesian-approach
#19
Chandrasekaran Kandhasamy, Kaushik Ghosh
Indian states are currently classified into HIV-risk categories based on the observed prevalence counts, percentage of infected attendees in antenatal clinics, and percentage of infected high-risk individuals. This method, however, does not account for the spatial dependence among the states nor does it provide any measure of statistical uncertainty. We provide an alternative model-based approach to address these issues. Our method uses Poisson log-normal models having various conditional autoregressive structures with neighborhood-based and distance-based weight matrices and incorporates all available covariate information...
February 2017: Spatial and Spatio-temporal Epidemiology
https://www.readbyqxmd.com/read/28125928/conditional-overdispersed-models-application-to-count-area-data
#20
Edilberto Cepeda-Cuervo, Michel Córdoba, Vicente Núñez-Antón
This paper proposes alternative models for the analysis of count data featuring a given spatial structure, which corresponds to geographical areas. We assume that the overdispersion data structure partially results from the existing and well justified spatial correlation between geographical adjacent regions, so an extension of existing overdispersion models that include spatial neighborhood structures within a Bayesian framework is proposed. These models allow practitioners to quantify the association explained by the considered neighborhood structures and the one modelled by additional factors...
January 1, 2017: Statistical Methods in Medical Research
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