{"title":"Exploratory Spatial Analysis of Relationships between Crimes and Socioeconomic Factors in St. Louis, Missouri","authors":"Tianyu Li","doi":"10.1007/s12061-025-09699-7","DOIUrl":null,"url":null,"abstract":"<div><p>St. Louis, Missouri as the major metropolitan area in the Midwest, has faced persistent challenges related to violent crimes and property crimes. Existing research suggests that crime and socioeconomic status influence each other; however, empirical studies specifically focused on the St. Louis area remain limited. This study utilized data on crime patterns across the St. Louis area to explore the complex interrelationships among five types of crime—assault, auto theft, burglary, homicide, and robbery—and various socioeconomic characteristics, including housing conditions, poverty levels, transportation access, educational attainment, and employment rates. An exploratory regression analysis was conducted to identify the independent variables that would construct the best-fitting model. Both Ordinary Least Squares (OLS) and Geographically Weighted Regression (GWR) results indicate that, whether considered collectively or individually, the five crime types do not fundamentally alter the overall relationship between crime and the selected socioeconomic factors. However, the socioeconomic factors affecting crime statistics varied by crime type, with each type being associated with different combinations of independent variables. Additionally, Multiscale Geographically Weighted Regression (MGWR) results reveal that model performance varies spatially across all crime types, with local R² values being higher on the east side of St. Louis city and gradually decreasing toward the west side of St. Louis county. Moreover, in zip codes to the north of downtown St. Louis, which are perceived as less safe than average, socioeconomic indicators are relatively poor. This suggests that policies should be formulated based on the spatial distribution of crime.</p></div>","PeriodicalId":46392,"journal":{"name":"Applied Spatial Analysis and Policy","volume":"18 3","pages":""},"PeriodicalIF":1.9000,"publicationDate":"2025-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Spatial Analysis and Policy","FirstCategoryId":"90","ListUrlMain":"https://link.springer.com/article/10.1007/s12061-025-09699-7","RegionNum":4,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENVIRONMENTAL STUDIES","Score":null,"Total":0}
引用次数: 0
Abstract
St. Louis, Missouri as the major metropolitan area in the Midwest, has faced persistent challenges related to violent crimes and property crimes. Existing research suggests that crime and socioeconomic status influence each other; however, empirical studies specifically focused on the St. Louis area remain limited. This study utilized data on crime patterns across the St. Louis area to explore the complex interrelationships among five types of crime—assault, auto theft, burglary, homicide, and robbery—and various socioeconomic characteristics, including housing conditions, poverty levels, transportation access, educational attainment, and employment rates. An exploratory regression analysis was conducted to identify the independent variables that would construct the best-fitting model. Both Ordinary Least Squares (OLS) and Geographically Weighted Regression (GWR) results indicate that, whether considered collectively or individually, the five crime types do not fundamentally alter the overall relationship between crime and the selected socioeconomic factors. However, the socioeconomic factors affecting crime statistics varied by crime type, with each type being associated with different combinations of independent variables. Additionally, Multiscale Geographically Weighted Regression (MGWR) results reveal that model performance varies spatially across all crime types, with local R² values being higher on the east side of St. Louis city and gradually decreasing toward the west side of St. Louis county. Moreover, in zip codes to the north of downtown St. Louis, which are perceived as less safe than average, socioeconomic indicators are relatively poor. This suggests that policies should be formulated based on the spatial distribution of crime.
期刊介绍：
Description
The journal has an applied focus: it actively promotes the importance of geographical research in real world settings
It is policy-relevant: it seeks both a readership and contributions from practitioners as well as academics
The substantive foundation is spatial analysis: the use of quantitative techniques to identify patterns and processes within geographic environments
The combination of these points, which are fully reflected in the naming of the journal, establishes a unique position in the marketplace.
RationaleA geographical perspective has always been crucial to the understanding of the social and physical organisation of the world around us. The techniques of spatial analysis provide a powerful means for the assembly and interpretation of evidence, and thus to address critical questions about issues such as crime and deprivation, immigration and demographic restructuring, retailing activity and employment change, resource management and environmental improvement. Many of these issues are equally important to academic research as they are to policy makers and Applied Spatial Analysis and Policy aims to close the gap between these two perspectives by providing a forum for discussion of applied research in a range of different contexts
Topical and interdisciplinaryIncreasingly government organisations, administrative agencies and private businesses are requiring research to support their ‘evidence-based’ strategies or policies. Geographical location is critical in much of this work which extends across a wide range of disciplines including demography, actuarial sciences, statistics, public sector planning, business planning, economics, epidemiology, sociology, social policy, health research, environmental management.
FocusApplied Spatial Analysis and Policy will draw on applied research from diverse problem domains, such as transport, policing, education, health, environment and leisure, in different international contexts. The journal will therefore provide insights into the variations in phenomena that exist across space, it will provide evidence for comparative policy analysis between domains and between locations, and stimulate ideas about the translation of spatial analysis methods and techniques across varied policy contexts. It is essential to know how to measure, monitor and understand spatial distributions, many of which have implications for those with responsibility to plan and enhance the society and the environment in which we all exist.
Readership and Editorial BoardAs a journal focused on applications of methods of spatial analysis, Applied Spatial Analysis and Policy will be of interest to scholars and students in a wide range of academic fields, to practitioners in government and administrative agencies and to consultants in private sector organisations. The Editorial Board reflects the international and multidisciplinary nature of the journal.
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