A comparison of the spatial dependence of body mass index among adults and children in a Swiss general population.

BACKGROUND: Body mass index (BMI) may cluster in space among adults and be spatially dependent. Whether BMI clusters among children and how age-specific BMI clusters are related remains unknown. We aimed to identify and compare the spatial dependence of BMI in adults and children in a Swiss general population, taking into account the area's income level. METHODS: Geo-referenced data from the Bus Santé study (adults, n=6663) and Geneva School Health Service (children, n=3601) were used. We implemented global (Moran's I) and local (local indicators of spatial association (LISA)) indices of spatial autocorrelation to investigate the spatial dependence of BMI in adults (35-74 years) and children (6-7 years). Weight and height were measured using standardized procedures. Five spatial autocorrelation classes (LISA clusters) were defined including the high-high BMI class (high BMI participant's BMI value correlated with high BMI-neighbors' mean BMI values). The spatial distributions of clusters were compared between adults and children with and without adjustment for area's income level. RESULTS: In both adults and children, BMI was clearly not distributed at random across the State of Geneva. Both adults' and children's BMIs were associated with the mean BMI of their neighborhood. We found that the clusters of higher BMI in adults and children are located in close, yet different, areas of the state. Significant clusters of high versus low BMIs were clearly identified in both adults and children. Area's income level was associated with children's BMI clusters. CONCLUSIONS: BMI clusters show a specific spatial dependence in adults and children from the general population. Using a fine-scale spatial analytic approach, we identified life course-specific clusters that could guide tailored interventions.

On the spatial convergence of (un)employment in Portugal

Regarding the EU policies of territorial cohesion is common to assume that, having the same been successful (in Portugal), regional disparities decreased. The purpose of this article is to assess the veracity of this allegation, for that considering the values of employment and unemployment rates by municipalities, determined in the last two censuses held in Portugal, i.e. 2001 and 2011. In doing so, spatial econometric techniques are used, namely local indicators of spatial association and spatial clusters, in order to better understand the eventual process of spatial convergence that may have occurred in Portugal in that period. The results point towards a spatial convergence of employment rates (both in total and by genres) and also of female unemployment rates but a spatial divergence of male unemployment rates.

Analysing and visualising areal crime data. A case study of residential burglary in San Francisco, USA

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

Estimating the extent of spatial association of Mycobacterium bovis infection in badgers in Ireland

Mycobacterium bovis infects the wildlife species badgers Meles meles who are linked with the spread of the associated disease tuberculosis (TB) in cattle. Control of livestock infections depends in part on the spatial and social structure of the wildlife host. Here we describe spatial association of M. bovis infection in a badger population using data from the first year of the Four Area Project in Ireland. Using second-order intensity functions, we show there is strong evidence of clustering of TB cases in each the four areas, i.e. a global tendency for infected cases to occur near other infected cases. Using estimated intensity functions, we identify locations where particular strains of TB cluster. Generalized linear geostatistical models are used to assess the practical range at which spatial correlation occurs and is found to exceed 6 in all areas. The study is of relevance concerning the scale of localized badger culling in the control of the disease in cattle.

Spatial distribution of disseminated histoplasmosis and AIDS co-infection in an endemic area of Northeastern Brazil

Abstract: INTRODUCTION: The spatial distribution of disseminated histoplasmosis (DH) and acquired immunodeficiency syndrome (AIDS) co-infection in adult residents of Fortaleza, Ceará, Brazil was evaluated. METHODS: Socio-demographic data for the DH/AIDS cases were obtained from a reference hospital, and socio-environmental indicators were obtained from an official Brazilian institute. Kernel analysis and local indicators of spatial autocorrelation (LISA) cluster maps were used to estimate the case density within the city. RESULTS: DH/AIDS cases were concentrated in the Northwestern and Southwestern peripheral areas of the city, related with low human development indices, but different from AIDS cases distribution. CONCLUSION: Risk factors other than AIDS infection must affect histoplasmosis development in this area.

Spatial autocorrelation of ndvi and gvi indices derived from landsat/tm images for soybean crops in the western of the state of Paraná in 2004/2005 crop season

This research aims at studying spatial autocorrelation of Landsat/TM based on normalized difference vegetation index (NDVI) and green vegetation index (GVI) of soybean of the western region of the State of Paraná. The images were collected during the 2004/2005 crop season. The data were grouped into five vegetation index classes of equal amplitude, to create a temporal map of soybean within the crop cycle. Moran I and Local Indicators of Spatial Autocorrelation (LISA) indices were applied to study the spatial correlation at the global and local levels, respectively. According to these indices, it was possible to understand the municipality-based profiles of tillage as well as to identify different sowing periods, providing important information to producers who use soybean yield data in their planning.

The spatial association of numbers and mathematical symbols

The "SNARC effect" refers to the finding that people respond faster to small numbers with the left hand and to large numbers with the right hand. This effect is often explained by hypothesizing that numbers are represented from left to right in ascending order (Mental Number Line). However, the SNARC effect may not depend on quantitative information, but on other factors such as the order in which numbers are often represented from left to right in our culture. Four experiments were performed to test this hypothesis. In the first experiment, the concept of spatial association was extended to nonnumeric mathematical symbols: the minus and plus symbols. These symbols were presented as fixation points in a spatial compatibility paradigm. The results demonstrated an opposite influence of the two symbols on the target stimulus: the minus symbol tends to favor the target presented on the left, while the plus symbol the target presented on the right, demonstrating that spatial association can emerge in the absence of a numerical context. In the last three experiments, the relationship between quantity and order was evaluated using normal numbers and mirror numbers. Although mirror numbers denote quantity, they are not encountered in a left-to-right spatial organization. In Experiments 1 and 2, participants performed a magnitude classification task with mirror and normal numbers presented together (Experiment 1) or separately (Experiment 2). In Experiment 3, participants performed a new task in which quantity information processing was not required: the mirror judgment task. The results show that participants access the quantity of both normal and mirror numbers, but only the normal numbers are spatially organized from left to right. In addition, the physical similarity between the numbers, used as a predictor variable in the last three experiments, showed that the physical characteristics of numbers influenced participants' reaction times.

Geographical and temporal distribution of human giardiasis in Ontario, Canada

Affiliation: Pascal Michel : Département de pathologie et microbiologie, Faculté de médecine vétérinaire, Université de Montréal

Measuring the degree of spatial correlation between histological features in thin sections of brain tissue

Histological features visible in thin sections of brain tissue, such as neuronal perikarya, blood vessels, or pathological lesions may exhibit a degree of spatial association or correlation. In neurodegenerative disorders such as AD, Pick's disease, and CJD, information on whether different types of pathological lesion are spatially correlated may be useful in elucidating disease pathogenesis. In the present article the statistical methods available for studying spatial association in histological sections are reviewed. These include tests of interspecific association between two or more histological features using χ2 contingency tables, measurement of 'complete' and 'absolute' association, and more complex methods that use grids of contiguous samples. In addition, the use of correlation matrices and stepwise multiple regression methods are described. The advantages and limitations of each method are reviewed and possible future developments discussed.

Is there a spatial association between senile plaques and neurofibrillary tangles in Alzheimer's disease?

Objective: To test the hypothesis that the clusters of senile plaques (SP) and neurofibrillary tangles (NFT) in patients with Alzheimer's disease (AD) are spatially associated as predicted by the 'Amyloid Cascade Hypothesis'. Methods: The spatial association between the SP and NFT was studied in the cerebral cortex and hippocampus in six cases of sporadic Alzheimer's disease (AD) using contingency tables. The coefficient C7 was used as an index of spatial association while chi-square with correction for continuity was used as a test of significance. Results: In the brain regions analysed, values of C7 were in the range -0.31 to +0.32 but a statistically significant spatial association between SP and NFT was present in only 8/39 (21%) regions. The degree of spatial association between the SP and NFT was similar in dfferent brain regions and did not vary with apolipoprotein ε genotype of the patient. However, the magnitude of C7 in a region was positively correlated with the density of the NFT and with the total density of SP and NFT but not with the density of SP alone. Conclusion: There was little evidence that SP and NFT were spatially associated except in brain areas with high densities of lesions. The data support the hypothesis that SP and NFT are distributed relatively independently in the cerebral cortex and hippocampus and therefore, could be distinct phenomena in AD.

Measuring the degree of spatial correlation between pathological lesions in Alzheimer's disease

The pathological lesions characteristic of Alzheimer's disease (AD), viz., senile plaques (SP) and neurofibrillary tangles (NFT) may not be randomly distributed with reference to each other but exhibit a degree of sptial association or correlation, information on the degree of association between SP and NFT or between the lesions and normal histological features, such as neuronal perikarya and blood vessels, may be valuable in elucidating the pathogenesis of AD. This article reviews the statistical methods available for studying the degree of spatial association in histological sections of AD tissue. These include tests of interspecific association between two or more histological features using chi-square contingency tables, measurement of 'complete' and 'absolute' association, and more complex methods that use grids of contiguous samples. In addition, analyses of association using correlation matrices and stepwise multiple regression methods are described. The advantages and limitations of each method are reviewed and possible future developments discussed.

Differentiation of soil properties related to the spatial association of wheat roots and soil macropores

Under certain soil conditions, e.g. hardsetting clay B-horizons of South-Eastern Australia, wheat plants do not perform as well as would be expected given measurements of bulk soil attributes. In such soils, measurement indicates that a large proportion (80%) of roots are preferentially located in the soil within 1 mm of macropores. This paper addresses the question of whether there are biological and soil chemical effects concomitant with this observed spatial relationship. The properties of soil manually dissected from the 1-3 mm wide region surrounding macropores, the macropore sheath, were compared to those that are measured in a conventional manner on the bulk soil. Field specimens of two different soil materials were dissected to examine biological differentiation. To ascertain whether the macropore sheath soil differs from rhizosphere soil, wheat was grown in structured and repacked cores under laboratory conditions. The macropore sheath soil contained more microbial biomass per unit mass than both the bulk soil and the rhizosphere. The bacterial population in the macropore sheath was able to utilise a wider range of carbon substrates and to a greater extent than the bacterial population in the corresponding bulk soil. These differences between the macropore sheath and bulk soil were almost non-existent in the repacked cores. Evidence for larger numbers of propagules of the broad host range fungus Pythium in the macropore sheath soil were also obtained.

Local influence for spatial analysis of soil physical properties and soybean yield using student's t-distribution

The modeling and estimation of the parameters that define the spatial dependence structure of a regionalized variable by geostatistical methods are fundamental, since these parameters, underlying the kriging of unsampled points, allow the construction of thematic maps. One or more atypical observations in the sample data can affect the estimation of these parameters. Thus, the assessment of the combined influence of these observations by the analysis of Local Influence is essential. The purpose of this paper was to propose local influence analysis methods for the regionalized variable, given that it has n-variate Student's t-distribution, and compare it with the analysis of local influence when the same regionalized variable has n-variate normal distribution. These local influence analysis methods were applied to soil physical properties and soybean yield data of an experiment carried out in a 56.68 ha commercial field in western Paraná, Brazil. Results showed that influential values are efficiently determined with n-variate Student's t-distribution.

Testate amoebae (thecamoebians) as indicators of aquatic mine impact

The environmental impacts of a single mine often remain local, but acidic and metal-rich acid mine drainage (AMD) from the waste materials may pose a serious threat to adjacent surface waters and their ecosystems. Testate amoebae (thecamoebian) analysis was used together with lake sediment geochemistry to study and evaluate the ecological effects of sulphidic metal mines on aquatic environments. Three different mines were included in the study: Luikonlahti Cu-mine in Kaavi, eastern Finland, Haveri Cu-Au mine in Ylöjärvi, southern Finland and Pyhäsalmi Zn-Cu-S mine in Pyhäjärvi, central Finland. Luikonlahti and Haveri are closed mines, but Pyhäsalmi is still operating. The sampling strategy was case specific, and planned to provide a representative sediment sample series to define natural background conditions, to detect spatial and temporal variations in mine impacts, to evaluate the possible recovery after the peak contamination, and to distinguish the effects of other environmental factors from the mining impacts. In the Haveri case, diatom analyses were performed alongside thecamoebian analysis to evaluate the similarities and differences between the two proxies. The results of the analyses were investigated with multivariate methods (direct and indirect ordinations, diversity and distance measure indices). Finally, the results of each case study were harmonized, pooled, and jointly analyzed to summarize the results for this dissertation. Geochemical results showed broadly similar temporal patterns in each case. Concentrations of ions in the pre-disturbance samples defined the natural baseline against which other results were compared. The beginning of the mining activities had only minor impacts on sediment geochemistry, mainly appearing as an increased clastic input into the lakes at Haveri and Pyhäsalmi. The active mining phase was followed by the metallic contamination and, subsequently, by the most recent change towards decreased but still elevated metal concentrations in the sediments. Because of the delay in the oxidation of waste material and formation of AMD, the most intense, but transient metal contamination phase occurred in the post-mining period at Luikonlahti and Haveri. At Pyhäsalmi, the highest metal contamination preceded effluent mitigation actions. Spatial gradients were observed besides the temporal evolution in both the pre-disturbance and mine-impacted samples from Luikonlahti and Pyhäsalmi. The geochemical gradients varied with distance from the main source of contaminants (dispersion and dilution) and with water depth (redox and pH). The spatial extent of the highest metal contamination associated with these mines remained rather limited. At Haveri, the metallic impact was widespread, with the upstream site in another lake basin found to be contaminated. Changes in thecamoebian assemblages corresponded well with the geochemical results. Despite some differences, the general features and ecological responses of the faunal assemblages were rather similar in each lake. Constantly abundant strains of Difflugia oblonga, Difflugia protaeiformis and centropyxids formed the core of these assemblages. Increasing proportions of Cucurbitella tricuspis towards the surface samples were found in all of the cases. The results affirmed the indicator value of some already known indicator forms, but such as C. tricuspis and higher nutrient levels, but also elicited possible new ones such as D. oblonga ‘spinosa’ and clayey substrate, high conductivity and/or alkalinity, D. protaeiformis ‘multicornis’ and pH, water hardness and the amount of clastic material and Centropyxis constricta ‘aerophila’ and high metal and S concentrations. In each case, eutrophication appeared to be the most important environmental factor, masking the effects of other variables. Faunal responses to high metal inputs in sediments remained minor, but were nevertheless detectable. Besides the trophic state of the lake, numerical methods suggested overall geochemical conditions (pH, redox) to be the most important factor at Luikonlahti, whereas the Haveri results showed the clearest connection between metals and amoebae. At Pyhäsalmi, the strongest relationships were found between Ca- and S-rich present loading, redox conditions and substrate composition. Sediment geochemistry and testate amoeba analysis proved to be a suitable combination of methods to detect and describe the aquatic mine impacts in each specific case, to evaluate recovery and to differentiate between the effects of different anthropogenic and natural environmental factors. It was also suggested that aquatic mine impacts can be significantly mitigated by careful design and after-care of the waste facilities, especially by reducing and preventing AMD. The case-specific approach is nevertheless necessary because of the unique characteristics of each mine and variations in the environmental background conditions.

Examining the large-scale spatial coherence of European drought using regional indicators of precipitation and streamflow deficit

Droughts tend to evolve slowly and affect large areas simultaneously, which suggests that improved understanding of spatial coherence of drought would enable better mitigation of drought impacts through enhanced monitoring and forecasting strategies. This study employs an up-to-date dataset of over 500 river flow time series from 11 European countries, along with a gridded precipitation dataset, to examine the spatial coherence of drought in Europe using regional indicators of precipitation and streamflow deficit. The drought indicators were generated for 24 homogeneous regions and, for selected regions, historical drought characteristics were corroborated with previous work. The spatial coherence of drought characteristics was then examined at a European scale. Historical droughts generally have distinctive signatures in their spatio-temporal development, so there was limited scope for using the evolution of historical events to inform forecasting. Rather, relationships were explored in time series of drought indicators between regions. Correlations were generally low, but multivariate analyses revealed broad continental-scale patterns, which appear to be related to large-scale atmospheric circulation indices (in particular, the North Atlantic Oscillation and the East Atlantic West Russia pattern). A novel methodology for forecasting was developed (and demonstrated with reference to the United Kingdom), which predicts drought from drought i.e. uses spatial coherence of drought to facilitate early warning of drought in a target region, from drought which is developing elsewhere in Europe.Whilst the skill of the methodology is relatively modest at present, this approach presents a potential new avenue for forecasting, which offers significant advantages in that it allows prediction for all seasons, and also shows some potential for forecasting the termination of drought conditions.