Fahui Wang

Street Centrality and Densities of Retail and Services in Bologna, Italy:

This paper examines the relationship between street centrality and densities of commercial and service activities in the city of Bologna, northern Italy. Street centrality is calibrated in a multiple centrality assessment model composed of multiple measures such as closeness, betweenness, and straightness. Kernel density estimation is used to transform datasets of centrality and activities to one scale unit for analysis of correlation between them. Results indicate that retail and service activities in Bologna tend to concentrate in areas with better centralities. The distribution of these activities correlates highly with the global betweenness of the street network, and also, to a slightly lesser extent, with the global closeness. This confirms the hypothesis that street centrality plays a crucial role in shaping the formation of urban structure and land uses.

Late-Stage Breast Cancer Diagnosis and Health Care Access in Illinois∗

The variations of breast cancer mortality rates from place to place reflect both underlying differences in breast cancer prevalence and differences in diagnosis and treatment that affect the risk of death. This article examines the role of access to health care in explaining the variation of late-stage diagnosis of breast cancer. We use cancer registry data for the state of Illinois by zip code to investigate spatial variation in late diagnosis. Geographic information systems and spatial analysis methods are used to create detailed measures of spatial access to health care such as convenience of visiting primary care physicians and travel time from the nearest mammography facility. The effects of spatial access, in combination with the influences of socioeconomic factors, on late-stage breast cancer diagnosis are assessed using statistical methods. The results suggest that for breast cancer, poor geographical access to primary health care significantly increases the risk of late diagnosis for persons living outside the city of Chicago. Disadvantaged population groups including those with low income and racial and ethnic minorities tend to experience high rates of late diagnosis. In Illinois, poor spatial access to primary health care is more strongly associated with late diagnosis than is spatial access to mammography. This suggests the importance of primary care physicians as gatekeepers in early breast cancer detection.

Street Centrality and the Location of Economic Activities in Barcelona

The paper examines the geography of three street centrality indices and their correlations with various types of economic activities in Barcelona, Spain. The focus is on what type of street centrality (closeness, betweenness and straightness) is more closely associated with which type of economic activity (primary and secondary). Centralities are calculated purely on the street network by using a multiple centrality assessment model, and a kernel density estimation method is applied to both street centralities and economic activities to permit correlation analysis between them. Results indicate that street centralities are correlated with the location of economic activities and that the correlations are higher with secondary than primary activities. The research suggests that, in urban planning, central urban arterials should be conceived as the cores, not the borders, of neighbourhoods.

Rural Reversal? Rural-Urban Disparities in Late-stage Cancer Risk in Illinois

Differences in late‐stage cancer risk between urban and rural residents are a key component of cancer disparities. Using data from the Illinois State Cancer Registry from 1998 through 2002, the authors investigated the rural‐urban gradient in late‐stage cancer risk for 4 major types of cancer: breast, colorectal, lung, and prostate.

Geographic Disparities in Accessibility to Food Stores in Southwest Mississippi

Disparities in accessibility to healthy food are a critical public-health concern. Poor access to reasonably priced, nutritious, and good-quality food may lead to poor diet and increase the risks of health problems such as obesity, diabetes, and cardiovascular diseases. This research advances the popular two-step floating catchment area (2SFCA) method by incorporating a kernel density (KD) function to form the ‘KD2SFCA method’. The study applies the method to measure the spatial access to food stores in southwest Mississippi, and examines the interaction between the spatial access and nonspatial factors. The research shows that neighborhoods with higher scores of urban socioeconomic disadvantage actually have better spatial accessibility to food stores; but higher percentages of carless households and lower income in some neighborhoods may compromise overall accessibility. Neighborhoods with stronger cultural barriers tend to be associated with poorer spatial accessibility. The study clearly differentiates spatial and nonspatial factors in access inequalities, and thus helps policy makers to design corresponding remedial strategies.

Analyzing Relatedness by Toponym Co‐Occurrences on Web Pages

This research proposes a method for capturing “relatedness between geographical entities” based on the co-occurrences of their names on web pages. The basic assumption is that a higher count of co-occurrences of two geographical places implies a stronger relatedness between them. The spatial structure of China at the provincial level is explored from the co-occurrences of two provincial units in one document, extracted by a web information retrieval engine. Analysis on the co-occurrences and topological distances between all pairs of provinces indicates that: (1) spatially close provinces generally have similar co-occurrence patterns; (2) the frequency of co-occurrences exhibits a power law distance decay effect with the exponent of 0.2; and (3) the co-occurrence matrix can be used to capture the similarity/linkage between neighboring provinces and fed into a regionalization method to examine the spatial organization of China. The proposed method provides a promising approach to extracting valuable geographical information from massive web pages.

Rural - urban inequalities in late-stage breast cancer: spatial and social dimensions of risk and access.

Rural – urban inequalities in health and access to health care have long been of concern in health-policy formulation. Understanding these inequalities is critically important in efforts to plan a more effective geographical distribution of public health resources and programs. Socially and ethnically diverse populations are likely to exhibit different rural – urban gradients in health and well-being because of their varying experiences of place environments, yet little is known about the interplay between social and spatial inequalities. Using data from the Illinois State Cancer Registry, we investigate rural – urban inequalities in late-stage breast cancer diagnosis both for the overall population and for African-Americans, and the impacts of socioeconomic deprivation and spatial access to health care. Changes over time are analyzed from 1988–92 to 1998–2002, periods of heightened breast cancer awareness and increased access to screening. In both time periods, the risk of late-stage diagnosis is highest among patients living in the most urbanized areas, an indication of urban disadvantage. Multilevel modeling results indicate that rural – urban inequalities in risk are associated with differences in the demographic characteristics of area populations and differences in the social and spatial characteristics of the places in which they live. For African-American breast cancer patients, the rural – urban gradient is reversed, with higher risks among patients living outside the city of Chicago, suggesting a distinct set of health-related risks and place experiences that inhibit early breast cancer detection. Findings emphasize the need for combining spatial and social targeting in locating cancer prevention and treatment programs.

Planning toward Equal Accessibility to Services: A Quadratic Programming Approach

In the literature various accessibility indices have been developed to assess the relative ease by which the locations of services (supply) can be reached from a residential (demand) location. In this paper we address the planning problem: how the resources can be redistributed to achieve the highest equality of accessibility to the service providers. In particular, a quadratic programming approach is used to minimize the variance of accessibility scores across demand locations by readjusting the amounts of service supplies. Two case studies—job access in Columbus, OH and primary healthcare access in Chicago, IL—are used to illustrate the method. The result suggests that in order to achieve better equality of accessibility, peripheral areas, in general, need additional supplies to compensate for their less-central locations, and some central city areas also need to add supplies to accommodate high demands by the high population density there.

Analyzing spatial aggregation error in statistical models of late-stage cancer risk: a Monte Carlo simulation approach.

PurposeThis paper examines the effect of spatial aggregation error on statistical estimates of the association between spatial access to health care and late-stage cancer.MethodsMonte Carlo simulation was used to disaggregate cancer cases for two Illinois counties from zip code to census block in proportion to the age-race composition of the block population. After the disaggregation, a hierarchical logistic model was estimated examining the relationship between late-stage breast cancer and risk factors including travel distance to mammography, at both the zip code and census block levels. Model coefficients were compared between the two levels to assess the impact of spatial aggregation error.ResultsWe found that spatial aggregation error influences the coefficients of regression-type models at the zip code level, and this impact is highly dependent on the study area. In one study area (Kane County), block-level coefficients were very similar to those estimated on the basis of zip code data; whereas in the other study area (Peoria County), the two sets of coefficients differed substantially raising the possibility of drawing inaccurate inferences about the association between distance to mammography and late-stage cancer risk.ConclusionsSpatial aggregation error can significantly affect the coefficient values and inferences drawn from statistical models of the association between cancer outcomes and spatial and non-spatial variables. Relying on data at the zip code level may lead to inaccurate findings on health risk factors.

Healthcare access, socioeconomic factors and late-stage cancer diagnosis: an exploratory spatial analysis and public policy implication

Patients diagnosed with late-stage cancer have lower survival rates than those with early-stage cancer. This paper examines possible associations between several risk factors and late-stage diagnosis for four types of cancer in Illinois: breast cancer, prostate cancer, colorectal cancer, and lung cancer. Potential risk factors are composed of spatial factors and nonspatial factors. The spatial factors include accessibility to primary healthcare and distance or travel time to the nearest cancer screening facility. A set of demographic and socioeconomic variables are consolidated into three nonspatial factors by factor analysis. The Bayesian model with convolution priors is utilised to analyse the relationship between the above risk factors and each type of late-stage cancer while controlling for spatial autocorrelation. The results for breast cancer suggest that people living in neighbourhoods with socioeconomic disadvantages and cultural barriers are more likely to be diagnosed at a late stage. In regard to prostate cancer, people in regions with low socioeconomic status are also more likely to be diagnosed at a late stage. Diagnosis of late-stage colorectal or lung cancer is not significantly associated with any of the abovementioned risk factors. The results have important implications in public policy.