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The study investigated the socio-demographic characteristics, community characteristics, sources of fear of crime, frequency of news of crime, sources of information on crime, length of stay in the community and perception of rate of crime as predictors of fear of crime among residents in selected communities in Lagos, Nigeria. The study used cross-sectional survey to collect data from 800 respondents, who were randomly selected from four purposively selected communities based on the level of perceived level of social disorganisation- Idi-Araba, Idi-Oro, and Mushin and Surulere. The data were analysed at both descriptive and quantitative analyses. The result revealed that the public sector employee account for approximately twice as much as other factors to the prediction of the fear of crime among the participants under reference. Similarly, ‘not afraid of becoming a victim of crime’ and information about local crime and crime prevention’ contributed two times more than other factors to the prediction of observed fear of crime. Frequency of news about crime, are approximately two times more likely to be predictive of fear of crime. The result revealed that sources of information on crime (such as direct experience, interpersonal communication and mass media are approximately three times more likely predictive of fear of crime when not augmented with other predictors of fear of crime. As for the socio-demographic factors, education and religion have decreasing impact on fear of crime whereas marital status hastens fear of crime with housewife being three times more likely predictive of fear of crime. Intervention should be targeted at the vulnerable group such as separated and divorced to alleviate their fear of crime. Also, how information on crime news is disseminated should be reconsidered to reduce fear of crime among the populace. Lastly, the study suggests a complete overhaul of the general requirements for the standardization and modernization of procedures of policing and involvement of community in crime prevention.

Crimes are pervasive with the potential to disrupt the community’s socio-economic activities and academic learning. The College of Medicine University of Lagos (CMUL) Idi-Araba campus neighbourhood is predominantly slum both in physical and social characteristics thus vulnerable to criminal activities. Mapping the distribution of human activities and other geographic features that are potential crime locations (PCLs) around the university environment has not been given extensive attention. This study uses Geographic Information Science (GIS) to identify PCLs within and around the CMUL neighbourhood. An intensive field campaign through Global Positioning System (GPS) deployment was carried out and collected data were processed and analyzed using buffer tool in ArcMap 10.8 GIS environment. Classification and ranking of human activities and other spatial features as PCLs were based on neighbourhood characteristics influencing crime while the proximity of law enforcement agencies was carried out at 500, 1000 and 1,500 meters’ buffers to the CMUL. Results show that five of the nine very high PCLs including motor parks and bus stops are within the 500m of the CMUL while fifteen (15) of the forty-two (42) high PCLs such as beer sale shops, banks, and motels are within 500m buffer. Only one of three police stations within the study area is a divisional headquarters while the other two are police posts. The current situation may embolden determined criminals to perpetrate activities to the detriment of academic learning. It is recommended that surveillance be mounted at the high PCLs and regular patrol of security agents within the study area should be put in place. Les crimes sont omniprésents et peuvent perturber les activités socio-économiques de la communauté et l’apprentissage scolaire. Le quartier du campus Idi-Araba du Collège de médecine de l’Université de Lagos (CMUL) est principalement un bidonville à la fois dans ses caractéristiques physiques et sociales, donc vulnérable aux activités criminelles. La cartographie de la répartition des activités humaines et d’autres caractéristiques géographiques qui sont des emplacements potentiels de criminalité (PCL) autour de l’environnement universitaire n’a pas fait l’objet d’une attention particulière. Cette étude utilise la science de l’information géographique (SIG) pour identifier les PCL à l’intérieur et autour du quartier CMUL. Une campagne intensive sur le terrain par le biais du déploiement du système de positionnement global (GPS) a été menée et les données collectées ont été traitées et analysées à l’aide de l’outil tampon dans l’environnement SIG ArcMap 10.8. La classification et le classement des activités humaines et d’autres caractéristiques spatiales en tant que LCP étaient basés sur les caractéristiques du quartier influençant la criminalité, tandis que la proximité des organismes d’application de la loi était effectuée à 500, 1000 et 1 500 mètres de tampons de la CMUL. Les résultats montrent que cinq des neuf PCL très élevés, y compris les parcs automobiles et les arrêts d’autobus, se trouvent à moins de 500 m de la CMUL, tandis que quinze (15) des quarante-deux (42) PCL élevées telles que les magasins de vente de bière, les banques et les motels se trouvent à moins de 500 m de zone tampon. Un seul des trois postes de police situés dans la zone d’étude est un quartier général divisionnaire, tandis que les deux autres sont des postes de police. La situation actuelle peut encourager les criminels déterminés à perpétrer des activités au détriment de l’apprentissage scolaire. Il est recommandé d’installer une surveillance aux LCP élevées et de mettre en place une patrouille régulière des agents de sécurité dans la zone d’étude.

The main objective of this study was to examine the influence of socio-demographic characteristics, community characteristics and fear of crime on self-reported health status among residents in selected communities in Lagos, Nigeria. The study was conducted in four selected communities in Lagos, namely Mushin, Idi-Oro, Idi-Araba and Surulere. Cross-sectional design survey was used to select 799 respondents using stratified sampling technique. Data were analysed at univariate, bivariate and ordinal logistic regression using SPSS version 22.0. Majority of the respondents rated their self-reported health status as excellent to good. The findings show that education increases the chances of achieving excellent to good selfreported health status; that female respondent reported excellent to good self-reported health status compared to the male respondents Also, Christians and Muslims reported excellent to good self-reported health status. Safely walking alone at night/day in the community positively affected self-reported health status. Fear of crime has direct relationship with self-reported health status. Sociodemographic, community characteristics and fear of crime influence self-reported health status. Policy on crime control should be specific at reducing fear of crime at individual and community levels to promote healthy individuals and communities.