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El estudio de la distribución de la población en el interior de los municipios rurales presenta importantes dificultades, derivadas de los reducidos volúmenes de población que muchos de ellos presentan, y que, a efectos prácticos, dejan al Padrón Municipal de Habitantes como la única fuente estadística a partir de la cual llevar a cabo este tipo de investigaciones. Desde la vertiente territorial estas dificultades son patentes en lo referente al empleo del seccionado censal, desde el momento en que, debido al escaso número de empadronados, la totalidad del término municipal queda embutida en una única sección, haciendo imposible, por tanto, conocer cómo se distribuye la población en su interior. Sin embargo, el empleo del Nomenclátor de Entidades y Núcleos de Población permite soslayar este escollo, por lo que su empleo se muestra como más conveniente en estos casos. Pero no sólo eso, desde el momento en que el Nomenclátor presenta la misma amplitud temática que el Padrón, también es posible no sólo indagar acerca de cómo se distribuye la población en el interior de los municipios, sino también dividirla en grupos a partir de alguna variable relevante, e indagar acerca de la distribución espacial intramunicipal de dichos grupos de población; tareas que no pueden ser llevadas a cabo a partir del seccionado, cuando éste tiene una única sección, y que, incluso siendo posible, hay ocasiones en las que la interpretación de la realidad queda desvirtuada por el trazado de los límites de las secciones. A partir de ejemplos de municipios rurales de la provincia de Málaga, en la presente investigación mostramos alguna de las principales ventajas que el Nomenclátor tiene sobre el seccionado censal. Para ello hemos empleado, por un lado, el volumen de población total, y su distribución entre nacidos en España y nacidos en el extranjero, datos procedentes de la Estadística del Padrón Continuo correspondientes a 2018; por otro, el seccionado censal de ese año, y la cartografía del Nomenclátor, también referida a 2018.The study of the spatial distribution of population within rural municipalities faces important difficulties, due to the small volumes of population that many of them present, leaving, at practical purposes, the Padron Municipal de Habitantes as the only statistical source to carry out this type of research. Taking into account the territorial aspect, these difficulties are evident when using census tracts, because when the population number is low, the entire municipal area is embedded in a single one, thus making impossible to know how it is distributed inside the municipality. However, the employment of the Nomenclator de Entidades y Núcleos de Población allows us to avoid this, so it is more convenient. Moreover, since the Nomenclator contains the same number of variables as the Padron, it is also possible not only to inquire about how the population is distributed within the municipalities, but also to divide it into groups using some relevant variable, and describe their intra-municipal spatial distribution. These tasks cannot be carried out using census tracts when only one is delimitated inside the municipality. Moreover, under some circunstances, the interpretation of reality is distorted by the layout of their boundaries. Based on examples of rural municipalities in the province of Malaga, in this paper we show some of the main advantages that the Nomenclator has over the census tract. To fullfill this objective, we have used both the total population volume, and its distribution among those born in Spain and born abroad, referred to 2018, and the census tracts and Nomenclator cartography, also referred to 2018.

Background Spatial variability of COVID-19 cases may suggest geographic disparities of social determinants of health. Spatial analyses of population-level data may provide insight on factors that may contribute to COVID-19 transmission, hospitalization, and death. Methods Generalized additive models were used to map COVID-19 risk from March 2020 to February 2021 in Orange County (OC), California. We geocoded and analyzed 221,843 cases to OC census tracts within a Poisson framework while smoothing over census tract centroids. Location was randomly permuted 1000 times to test for randomness. We also separated the analyses temporally to observe if risk changed over time. COVID-19 cases, hospitalizations, and deaths were mapped across OC while adjusting for population-level demographic data in crude and adjusted models. Results Risk for COVID-19 cases, hospitalizations, and deaths were statistically significant in northern OC. Adjustment for demographic data substantially decreased spatial risk, but areas remained statistically significant. Inclusion of location within our models considerably decreased the magnitude of risk compared to univariate models. However, percent minority (adjusted RR: 1.06, 95%CI: 1.06, 1.07), average household size (aRR: 1.06, 95%CI: 1.05, 1.07), and percent service industry (aRR: 1.05, 95%CI: 1.04, 1.06) remained significantly associated with COVID-19 risk in adjusted spatial models. In addition, areas of risk did not change between surges and risk ratios were similar for hospitalizations and deaths. Conclusion Significant risk factors and areas of increased risk were identified in OC in our adjusted models and suggests that social and environmental factors contribute to the spread of COVID-19 within communities. Areas in north OC remained significant despite adjustment, but risk substantially decreased. Additional investigation of risk factors may provide insight on how to protect vulnerable populations in future infectious disease outbreaks.

This study examines the relationship between multidimensional vulnerability and COVID-19 infection rates across Malaga’s census tracts for the period February 2020 to February 2021. Malaga is a cosmopolitan tourist destination on the southern Mediterranean coast that has the sixth largest population in Spain. The analysis uses high frequency (daily) data on the accumulated incidence of the disease at 14 days and shows that COVID-19 did not spread symmetrically across the census tracts of Malaga but had a greater impact on the most vulnerable neighbourhoods. However, the pattern of this relationship was not uniform in the period examined, with specific contextual factors driving the higher infection rates across time. Our findings show that pandemic containment regulations cannot overlook vulnerability considerations and universal restrictions to reduce the spread of disease should be supplemented by targeted regulations for specific areas.

Limited access to foodstores or other sources of healthy and affordable food may impede the ability of some people living in the United States to eat a healthy diet. Income, vehicle access, and distance to the nearest foodstore may be barriers to food access for some. This report updates estimates of low-income and low-foodstore-access census tracts—as found in USDA, Economic Research Service’s Food Access Research Atlas—using a 2019 directory of foodstores and 2014–18 American Community Survey data on household vehicle access and family income. The number of census tracts classified as low income (LI), based on the poverty rate and median income, decreased by 2 percent from 2015 to 2019. The number of census tracts classified as low access (LA) decreased for two out of three measures solely based on distance. For the fourth measure accounting for vehicle access, the number of LA census tracts shrank by 6.4 percent from 2015 to 2019. This decrease largely reflects higher levels of vehicle access across all U.S. housing units relative to 2015. Overlapping LI and LA tracts resulted in decreases in the number of low-income, low-access (LILA) tracts for two measures and increases in two measures. Overall, 33.2 percent of low-income individuals—those who have annual family income at or below 200 percent of the Federal poverty threshold for family size—lived more than 1 mile from the nearest supercenter, supermarket, or large grocery store. Furthermore, 33.6 percent of households participating in the USDA Supplemental Nutrition Assistance Program (SNAP) lived more than 1 mile from a food-store in 2019 compared with 34.2 percent in 2015.

In the first year of the COVID-19 pandemic, Spain was one of the worst-hit countries, although not all areas and social groups were affected equally. This study focuses on Malaga, a cosmopolitan tourist destination located on the southern Mediterranean coast that has the sixth largest population in Spain. Specifically, it examines the relationship between multidimensional vulnerability and COVID-19 infection rates across the city’s census tracts for the period February 2020 to February 2021. The analysis uses high frequency (daily) data on the accumulated incidence of the disease at 14 days and shows that COVID-19 did not spread symmetrically across the census tracts of Malaga but had a greater impact on the most vulnerable neighbourhoods. However, the pattern of this relationship was not uniform in the period examined, with specific contextual factors driving the higher infection rates across time. Our findings show that pandemic containment regulations cannot overlook vulnerability considerations and universal restrictions to reduce the spread of disease should be supplemented by targeted regulations for specific areas. This work was supported by the Junta de Andalucía, under the grant FEDER-COVID (CV20-27760) for the project “Vulnerabilidad y resiliencia post-COVID en el área metropolitana de Málaga” and Universidad de Málaga. We thank the funding for open access charge to Universidad de Málaga / CBUA.

Background Area-level measures are often used to approximate socioeconomic status (SES) when individual-level data are not available. However, no national studies have examined the validity of these measures in approximating individual-level SES. Methods Data came from ~ 3,471,000 participants in the Mortality Disparities in American Communities study, which links data from 2008 American Community Survey to National Death Index (through 2015). We calculated correlations, specificity, sensitivity, and odds ratios to summarize the concordance between individual-, census tract-, and county-level SES indicators (e.g., household income, college degree, unemployment). We estimated the association between each SES measure and mortality to illustrate the implications of misclassification for estimates of the SES-mortality association. Results Participants with high individual-level SES were more likely than other participants to live in high-SES areas. For example, individuals with high household incomes were more likely to live in census tracts (r = 0.232; odds ratio [OR] = 2.284) or counties (r = 0.157; OR = 1.325) whose median household income was above the US median. Across indicators, mortality was higher among low-SES groups (all p < .0001). Compared to county-level, census tract-level measures more closely approximated individual-level associations with mortality. Conclusions Moderate agreement emerged among binary indicators of SES across individual, census tract, and county levels, with increased precision for census tract compared to county measures when approximating individual-level values. When area level measures were used as proxies for individual SES, the SES-mortality associations were systematically underestimated. Studies using area-level SES proxies should use caution when selecting, analyzing, and interpreting associations with health outcomes.

to produce for the national territory as a whole a deprivation index (ID) at the census section level, based on 2011 census data, in the same way as the Italian index based on the 2001 census, revising the formulation of some indicators.the study uses the individual data of the general population and housing census of 2011. For the calculation of the index five conditions were chosen that best describe the multidimensional concept of social and material deprivation: low level of education, being unemployed, living in rent, living in crowded house, living in a single-parent family. The index is calculated as the sum of standardized indicators and is also available categorized into quintiles. Compared to the previous formulation of the ID, the proposed revised ID made use of a low education indicator limited to the age group 15-60; for what concerns single-parent families, only the cohabitations with minor children is considered.reformulated ID and comparison measures between the two indices (correlation, kappa statistic).the revised index, compared with the previous one, a different quintile distribution for a significant share of census sections, with the exception of the first and fifth quintiles (that of the least deprived and the most deprived ones).given that in this field of study should be taken for granted the inexistence of a method that produces results objectively and universally valid, the review of the index proposed in this study starts from the availability of analytical data that allowed to overcome some constraints that had induced the choices of the ID proposed in 2010. Anyway, both the original and the revised index produce reliable and consistent results.

Overlapping maps in different scales is associatedgeometric problems, ecological fallacy and change of support problem. This research analyzes researches published (2014-2019) in the top Brazilian geography journals which are related to the change of support problem. Besides providing evidence that shows the relevance of this problem to geography, this research goal is to propose a procedure that, by making maps in different scales compatible, reduces problems of spatial support change. The procedure is performed on a Freeware of Geographic Information System (GIS) and comprises: (i) inserting more vertices in the maps elements of census tracts (STs) of Brazilian Institute of Geography and Statistics or IBGE and the streets of Foz do Iguaçu-PR; and (ii) replace the vertices coordinates that present possible overlapping errors. Besides making 87% of Sts compatible to the streets, and presenting adjustment errors in only 2.81% of cases, the procedure does not require anyalgorithms or codes development, which are necessary in previous studies. A sobreposição de mapas em diferentes escalas está associada a problemas geométricos, da falácia ecológica e da mudança de suporte espacial. Essa pesquisa analisa trabalhos publicados (2014-2019) nas principais revistas de geografia do Brasil que se inserem no contexto do problema da mudança de suporte de dados geográficos. Além de trazer evidências que mostram a relevância desse problema para área da geografia, esse artigo tem como objetivo propor um procedimento que, ao compatibilizar mapas em diferentes escalas, reduz problemas de mudança de suporte espacial. O procedimento é realizado em software de Sistema de Informações Geográficas (SIG) livre e consiste em: (i) inserir mais vértices nos elementos dos mapas de Setores Censitários (SCs) do Instituto Brasileiro de Geografia e Estatística (IBGE) e do arruamento da cidade de Foz do Iguaçu-PR; e (ii) substituir as coordenadas dos vértices que apresentam possíveis erros de sobreposição. Além de compatibilizar 87% dos SCs, e apresentar erros de ajuste em 2,81% dos casos, o procedimento dispensa o desenvolvimento de algoritmos ou codificações, que são necessários em propostas anteriores.

Small cities across North America are experiencing rapid changes, but methodological obstacles hamper researchers’ ability to analyze them. This research note explores some of the methodological challenges faced by researchers and offers solutions. Using Charlottetown, Prince Edward Island, as a case study, we show that a major challenge lies in choosing meaningful geographic units for small city neighborhoods, and we evaluate the benefits and drawbacks of several geographical options. Another major challenge is that the boundaries of existing units change between census years, demanding an approach to reconstructing them to allow for temporal analysis. We propose two feasible solutions for re-creating neighborhood geographic units over time: ‘moving forward’ and ‘going backward.’ Both involve selecting units from a particular census year to serve as a fixed point of reference for the re-creation of boundaries across multiple census years. We conclude by cautioning that studying changes in small cities over longer time periods in Canada is not feasible because of the extensive and complex boundary changes that have occurred between census years. We offer an approach for looking at shorter time periods. SSHRC Insight Grant

Theoretical frameworks in environmental inequality suggest that affluent, white, and educated communities have a greater ability to control local environmental change. With a focus on neighborhood-level land development, the authors evaluate this proposition considering the spatial shifts that are reshaping metropolitan areas across the United States at the beginning of the twenty-first century. With coverage for 52,473 metropolitan census tracts, the authors integrate sociodemographic variables from governmental sources with longitudinal data on developed land area from the National Land Cover Database, 2001–2011. Controlling for a host of other factors, results from spatial regression models with fixed effects show that new land development is negatively associated with affluence and educational attainment. Situating the notion of environmental privilege in a historical context, we propose that, with the “back to the city” movement, these groups are moving back into the urban core, which is already relatively built-out and thus has a lower rate of new land development.

The three-generational household was a focal point of concern for school and community the Coronavirus Disease 2019 (COVID-19) transmission. The current study, using small area data and household variables, reported an approach to neighborhood-level COVID-19 mitigation for school reopening and communities returning to normalcy. The study started with an age-stratified Poisson regression to examine the association between the proportion of three-generational households and COVID-19 infection rates based on data from 74 census tracts in Lancaster County, Nebraska, U.S. from March 5, 2020 to August 22, 2020, followed by mapping the model-based risk score by census tract in the study area. We explored the feasibility of using COVID-19 infection rates and vaccination rates to inform decision-making on school opening from March 5, 2020 to February 3, 2021. The overall infection rate increased by 3% for every unit increased in the percentage of three-generational households after controlling for other covariates in the model. The census tracts were classified into low-, medium-, and high-priority neighborhoods for potential community-based interventions, such as targeted messages for household hygiene and isolation strategies.

Estudos mostram que existem diferentes abordagens para se medir a desigualdade de renda. Contudo, faltam análises empíricas que apliquem as diferentes formulações a uma mesma unidade de análise, demonstrando as implicações da alteração da escala de análise nos seus resultados. A partir dessa constatação, neste artigo, são apresentadas diferentes medidas de desigualdade de renda aplicadas em diferentes escalas (cidade e setores censitários urbanos). Os resultados sugerem que os setores censitários, ao concentrarem famílias de renda semelhante, tendem a ser menos desiguais internamente e mais desiguais na inter-relação com outros setores. Concluí-se que a medida de desigualdade de renda é sensível à escala de análise. Distorções significativas no índice de desigualdade de renda provocadas pela alteração da escala desfavorecem as comparações do índice entre diferentesescalas, mas, ao mesmo tempo, favorecem a inferência do grau da desigualdade de renda intraurbana Studies show that there are different approaches to measuring income inequality. However, there is a lack of empirical analyses realized for different approaches, applied to the same unit of analysis, demonstrating the implications of changing the scale of analysis in its results. From this statement, in this paper, we present different measures of income inequality applied at different scales (city and urban census tracts). The results show that the census tracts with concentrating families of similar income, tend to be less unequal internally and more unequal in the interrelationship with other sectors. It is concluded that the measure of income inequality is sensitive to the scale of analysis. Significant distortions in the income inequality index caused by the change in the scale disfavor the comparisons of the index between different scales, but, at the same time, favor the inference of the degree of intra-urban income inequality.

The purpose of this research was to investigate rural-urban differences in participation rates in three modes of active commuting (AC) and their built environmental correlates. The 2010 Census supplemented with other datasets were used to analyze AC rates in percent of workers age 16+ walking, biking, or taking public transportation to work in 70,172 Census tracts, including 12,844 rural and 57,328 urban. Random-intercept factional logit regressions were used to account for zero-inflated data and for clustering of tracts within counties. We found that the average AC rates were 3.44% rural and 2.77% urban (p, Highlights • The average active commuting prevalence in all U.S. tracts is 2.89%, 0.55%, and 4.89% for walking, biking, and public transportation to work around 2010, respectively. • Rural tracts have a higher prevalence of walking but lower prevalence of biking and public transportation to work than urban tracts. • Rural-urban differences in the associations between AC and environment are complex, with some variables showing opposite correlational directions, such as street connectivity for walking to work and population density for both walking to work and public transportation to work. • In developing strategies to promote AC, attention needs to be paid to rural-urban differences in order to avoid unintended consequences of “one-size fit all” type of approaches.

Les ciutats són llocs de contrastos. Al llarg de la història han anat modificant la seva morfologia i, en conseqüència, la manera i les formes de viure de la seva població. En el cas de Barcelona, aquesta evolució ha avançat cap a una ciutat de desigualtats entre barris i districtes fins al punt que determinats àmbits geogràfics concentren uns grups poblacionals concrets. El present estudi analitza i interpreta les característiques sociodemogràfiques de la població dels districtes de Les Corts i Nou Barris (molt heterogenis entre ells) per tal de trobar patrons que permetin agrupar la població segons els seus atributs socials, econòmics, demogràfics i espacials. Es tracta, doncs, de conèixer com són les persones que resideixen en un àmbit concret i quins són els atributs que comparteixen, agrupant-les i anant més enllà dels límits urbanístics i administratius que divideixen la ciutat actual. Las ciudades son lugares de contrastes. A lo largo de la historia han ido modificando su morfología y, en consecuencia, la manera y las formas de vivir de su población. En el caso de Barcelona, esta evolución ha avanzado hacia una ciudad de desigualdades entre barrios y distritos hasta el punto de que determinados ámbitos geográficos concentran unos grupos poblacionales concretos. El presente estudio analiza e interpreta las características sociodemográficas de la población de los distritos de Les Corts i Nou Barris (muy heterogéneos entre ellos) para encontrar patrones que permitan agrupar la población según sus atributos sociales, económicos, demográficos y espaciales. Se trata, pues, de conocer como son las personas que residen en un ámbito concreto y cuáles son los atributos que comparten, agrupándolas y yendo más allá de los límites urbanísticos y administrativos que dividen la ciudad actual. Cities are places of contrasts. Throughout history they have been modifying their morphology and, consequently, the way and ways of living of their population. In the case of Barcelona, this evolution has progressed towards a city of inequalities between neighbourhoods and districts to the point that certain geographical areas consolidate specific population groups. This study analyses the sociodemographic characteristics of the population of Les Corts and Nou Barris districts (two very heterogeneous districts between them) to find patterns that allow the population to be grouped according to their social, economic, demographic and spatial attributes. Knowing how the people are who reside in a specific area and what are the attributes they share, grouping them and going beyond the urban and administrative limits that divide the current city.

Aquest treball de fi de grau es basa en una anàlisi sociodemogràfic de tres municipis diferents, Castelldefels, Gavà i Viladecans, a través de les seccions censals. L'objectiu és trobar semblances i diferències entre aquests tres municipis a partir de dades sociodemogràfiques del Cens de Població i Habitatge i les Cobertes del Sòl i observar com és la població, no pas on viu. Els resultats són expressats a través de diferents mapes generats a partir de les dades. Este trabajo de fin de grado se basa en un análisis sociodemografico de tres municipios diferentes, Castelldefels, Gavà y Viladecans a partir de las secciones censales. El objetivo es encontrar parecidos y diferencias entre estos tres municipios a partir de datos sociodemograficos del Censo de Población y Vivienda i Cubiertas del Suelo y observar como es la población, no donde vive. Los resultados son representados a partir de diferentes mapas generados gracias a los datos. This final degree project is based on a socio-demographic analysis of three different municipalities, Castelldefels, Gavà and Viladecans, through the census tracts . The aim is to find similarities and differences between these three municipalities based on socio-demographic data from the Population and Housing Census and Land Cover and to observe what the population is like, not where it lives. The results are expressed through different maps generated from the data.

Due to the lack of a number of inhabitants at the time of the study in the Metropolitan District of Quito (DMQ), considering ages from them 10 to 65, the study area was delimited taking as base the population Census INEC from the year 2010, through the selection of the census tracts in urban land classification to obtain an approximation of the population size, about 1655073. The study was held by stratified sampling with proportional affixation to the size, considering the Census polygons sub-forming cells throughout the district, a grid composed of 400*400 square meters cells, considered as the walking area, which were analyzed as strata. The total number of cells was 2824. For the stratified division of the Metropolitan District of Quito it was considered the population density of each cell to determine the number of surveys, excluding green areas, parks, ravines, stadiums and large-scale educational facilities, because they do not have population significance. A total of 10503 surveys were georeferenced by the lot identification number as a result. It was determined the weight of the strata within the population universe of the DMQ in urban land, setting the number of surveys that apply within each cell for purposes of the analysis of consumption, commuting and local identity. Particularly it is highlighted the following results: a total of 25 surveys to be applied in 27 cells and 33 surveys in 2 cells, which evidence these spaces as the ones with the highest local density within the DMQ. Al no tener a la fecha del estudio un número exacto de habitantes en el Distrito Metropolitano de Quito (DMQ), contemplada desde los 10 hasta los 65 años de edad, se delimitó el área del estudio tomando como base el Censo Poblacional INEC del año 2010, mediante la selección de los polígonos censales en suelo de clasificación urbana para obtener una aproximación del tamaño de población de 1655073. Se realizó mediante Muestreo Estratificado con afijación proporcional al tamaño de subpolígonos censales: celdas en todo el Distrito, de 400*400 metros cuadrados considerada como el área caminable, los cuales fueron analizados como estratos resultando un total de 2824 celdas. Para la división estratificada del Distrito Metropolitano de Quito se consideró la densidad poblacional de cada celda para determinar el número de encuestas, excluyendo las áreas verdes, parques, quebradas, estadios y centros educativos de gran extensión por no tener significancia poblacional. Obteniendo un total de 10503 encuestas georreferenciadas por el número identificador de lote. Se determinó el peso de los estratos dentro del universo poblacional del DMQ en suelo urbano, estableciendo el número de encuestas que se debe aplicar dentro de cada celda para efectos del análisis de consumo, desplazamientos e identidad local. En particular se destacan los siguientes resultados: 25 encuestas a ser aplicadas en 27 celdas y 33 encuestas en 2 celdas, evidenciando estos como los espacios donde se está la mayor densidad local dentro del DMQ.

Research that attempts to characterize urban form is confronted with two key issues: criticism of the use of aggregate units of analysis, such as census tracts, and a general lack of consideration of variables related to elements other than the built environment, such as residents’ behavior. This methodological study explores the impact of travel behavior variables in the quantitative characterization of urban form at the census tract level for the Montreal region. Two separate factor-cluster analyses are performed: the first includes built-environment variables commonly used to typify areas within a region, and a second includes additional travel behavior variables. The results of both models are compared to satellite images to determine which analysis more accurately represents the reality on the ground. The results provide empirical evidence that travel behavior variables, in addition to built form, provide a more accurate representation of urban form at the census tract level. These variables refine the model output by moderating the effect of features that generally led to misleading results. This effect is particularly evident in areas represented by large census tracts. These results suggest that considering both built environment and behavioral characteristics in an analysis of urban form yields more precise results at the (aggregate) census tract level. The findings from this study could be helpful for engineers and planners when conducting property value studies, urban investment analysis, and policy intervention prioritization and when expanding the well-known land use classification of urban and rural categories.

Research that attempts to characterize urban form is confronted with two key issues: criticism of the use of aggregate units of analysis, such as census tracts, and a general lack of consideration of variables related to elements other than the built environment, such as residents’ behavior. This methodological study explores the impact of travel behavior variables in the quantitative characterization of urban form at the census tract level for the Montreal region. Two separate factor-cluster analyses are performed: the first includes built-environment variables commonly used to typify areas within a region, and a second includes additional travel behavior variables. The results of both models are compared to satellite images to determine which analysis more accurately represents the reality on the ground. The results provide empirical evidence that travel behavior variables, in addition to built form, provide a more accurate representation of urban form at the census tract level. These variables refine the model output by moderating the effect of features that generally led to misleading results. This effect is particularly evident in areas represented by large census tracts. These results suggest that considering both built environment and behavioral characteristics in an analysis of urban form yields more precise results at the (aggregate) census tract level. The findings from this study could be helpful for engineers and planners when conducting property value studies, urban investment analysis, and policy intervention prioritization and when expanding the well-known land use classification of urban and rural categories.

Location information regarding the surveyed units, for example, of households, establishments and enterprises, has been collected in surveys as area information, such as tract codes. The traditional location codes do not support the one-to-one correspondences between the unit and its location information, despite the fact that each unit has inherent unique positional information in terms of its location. This paper discusses the following issues. Firstly, it portrays a rough historical sketch on how location information of the surveyed units has been captured in surveys. Then it discusses several constraints in using survey results which the ambiguity of the data due to the insufficiently obtained positional information under questionnaire-based surveys gives rise to. Latest developments in information technology have opened up a new arena for the application of GPS also for statistical purposes. Rest of the paragraphs will highlight a breakthrough in regional analyses that will render the GPSed records more practical.

This paper proposes a method to match statistical data from urban census tracts of 1991 and 2000 using techniques of geoprocessing , with subsequent application to the study on population dynamics of Belem Metropolitan Area (BMA). This method aims to be applied in places where the boundaries of census tracts changed between the two years, which makes impossible a direct comparison between them. The methodology is developed from the implementation of a geographic information system (GIS) using the program TerraView/INPE, with three main layers of information: the census tracts meshes of the two years, with their statistics, and a network of orthogonal points distant 100m from each other, covering the two meshes. The operational procedure is based on the capture of statistical information of the census tracts of 1991 by the points network, followed by the transfer of information to the census tracts of 2000. The outcome is the same spatial base for both years, allowing comparison between them. The results identified, in detail, changes in population in various parts of the study area, and indicate that the population dynamics of BMA followed, in general, the main trends observed in other large cities of Brazil.

Background In New Haven County, CT (NHC), influenza hospitalization rates have been shown to increase with census tract poverty in multiple influenza seasons. Though multiple factors have been hypothesized to cause these inequalities, including population structure, differential vaccine uptake, and differential access to healthcare, the impact of each in generating observed inequalities remains unknown. We can design interventions targeting factors with the greatest explanatory power if we quantify the proportion of observed inequalities that hypothesized factors are able to generate. Here, we ask if population structure is sufficient to generate the observed area-level inequalities in NHC. To our knowledge, this is the first use of simulation models to examine the causes of differential poverty-related influenza rates. Methods Using agent-based models with a census-informed, realistic representation of household size, age-structure, population density in NHC census tracts, and contact rates in workplaces, schools, households, and neighborhoods, we measured poverty-related differential influenza attack rates over the course of an epidemic with a 23 % overall clinical attack rate. We examined the role of asthma prevalence rates as well as individual contact rates and infection susceptibility in generating observed area-level influenza inequalities. Results Simulated attack rates (AR) among adults increased with census tract poverty level (F = 30.5; P

International audience; In France, reducing social health inequalities has become an explicit goal of health policies over the past few years, one of its objectives is specifically the reduction of the perinatal mortality rate. This study investigates the association between infant mortality and social deprivation categories at a small area level in the Lille metropolitan area, in the north of France, to identify census blocks where public authorities should prioritize appropriate preventive actions. We used census data to establish a neighbourhood deprivation index whose multiple dimensions encompass socioeconomic characteristics. Infant mortality data were obtained from the Lille metropolitan area municipalities to estimate a death rate at the census tract level. We used Bayesian hierarchical models in order to reduce the extra variability when computing relative risks (RR) and to assess the associations between infant mortality and deprivation. Between 2000 and 2009, 668 cases of infant death occurred in the Lille metropolitan area (4.2 per 1,000 live births). The socioeconomic status is associated with infant mortality, with a clear gradient of risk from the most privileged census blocks to the most deprived ones (RR = 2.62, 95 % confidence interval [1.87; 3.70]). The latter have 24.6 % of families who were single parents and 29.9 % of unemployed people in the labor force versus 8.5 % and 7.7 % in the former. Our study reveals socio-spatial disparities in infant mortality in the Lille metropolitan area and highlights the census blocks most affected by the inequalities. Fine spatial analysis may help inform the design of preventive policies tailored to the characteristics of the local communities.

USDA’s Economic Research Service previously identified more than 6,500 food desert tracts in the United States based on 2000 Census and 2006 data on locations of supermarkets, supercenters, and large grocery stores. In this report, we examine the socioeconomic and demographic characteristics of these tracts to see how they differ from other census tracts and the extent to which these differences influence food desert status. Relative to all other census tracts, food desert tracts tend to have smaller populations, higher rates of abandoned or vacant homes, and residents who have lower levels of education, lower incomes, and higher unemployment. Census tracts with higher poverty rates are more likely to be food deserts than otherwise similar low-income census tracts in rural and in very dense (highly populated) urban areas. For less dense urban areas, census tracts with higher concentrations of minority populations are more likely to be food deserts, while tracts with substantial decreases in minority populations between 1990 and 2000 were less likely to be identified as food deserts in 2000.

This study investigates (i) the link of land use and road design on pedestrian safety and (ii) the effect of the level of spatial aggregation on the frequency of pedestrian accidents. For this purpose, pedestrian accident frequency models were developed for New York City based on an extensive dataset collected from different sources over a period of 5 years. The assembled dataset provides a rich source of variables (land-use, demographics, transit supply, road network and travel characteristics) and two different crash frequency outcomes: total and fatal-only collision counts. Among other things, it was observed that the census tract analysis (disaggregate data) provides more insightful and consistent results than the analysis at the zip code level. The results indicate that tracts with greater fraction of industrial, commercial, and open land use types have greater likelihood for crashes while tracts with a greater fraction of residential land use have significantly lower likelihood of pedestrian crashes. Moreover, census tracts that have a greater number of schools and transit stops - which are determinants of pedestrian activity - are more likely to have greater crashes. Results also show that the likelihood of pedestrian-vehicle collision increases with the number of lanes and road width. This suggests that retrofitting or narrowing the roads could possibly reduce the risk of pedestrian crashes. � 2011 Elsevier Ltd.

There are two questions raised when looking at the spatial pattern of the rate of bankruptcies in Utah: (i) are there similarities between the bankruptcy data in adjacent census tracts and (ii) can local cluster and outliers be identified within the data? Specifically, are there similar rates of bankruptcies in bordering census tracts and are there any localized areas of interest where we find extremely high or extremely low rates of bankruptcies? This study uses spatial statistics to perform tests for spatial autocorrelation to address these two questions. It also looks at commonalities in the clusters and differences in the outliers. Using a spatial statistical approach, insight is gained regarding the relationship of bankruptcies between census tracts in Utah and how strong that spatial autocorrelation may be.