Exploring the Relationship Between Socio-Economic Factors and The Spatial Distribution of Crime in Nigeria
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Date
2025-12
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Department of Geography and Environmental Management, University of Ilorin
Abstract
Crime poses a major threat to human survival, causing both physical harm and property loss, while also increasing victims' feelings of vulnerability and insecurity. This research investigates the spatial distribution of crimes across Nigeria and examines how socio-economic characteristics influence crime rates. Using data from the National Bureau of Statistics (2017, 2018, 2020), Ordinary Least Squares linear regression was conducted within the ArcGIS 10.5 environment to assess how socio-economic variables of different states impact crime rates. Findings revealed that Lagos and Abia states recorded the highest rates of crimes against persons, at 247.12 and 148.76 per 100,000 persons, respectively. Findings also highlighted that states such as Kebbi, Anambra, Bauchi, Kogi, Zamfara, Kaduna, Jigawa, Rivers, Osun, Benue, and Katsina recorded significantly lower rates, ranging between 1.94 and 7.43 per 100,000 persons. Property offenses were highest in the Federal Capital Territory and Lagos, ranging from 91.72 to 211.91 per 100,000 persons, while the lowest rates were recorded in Kebbi, Kogi, Bauchi, Jigawa, and Zamfara states. Lagos also had the highest offenses against lawful authority, with 55.49 offenses per 100,000 persons. The findings further revealed a significant correlation between population density, educational index, and rates of crimes against persons and property. Notably, offenses against lawful authority yielded the best model performance with the lowest Akaike's Information Criterion (225.32) and the highest adjusted R-squared value (0.79). To mitigate crime, the study recommends that the Federal Government expand social and economic activities and services, while increasing state security personnel in response to rising population density.
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Keywords
Criminal Offences, Socio-economic factors, Ordinary Least Squares, Population density, Spatial Distribution