DSpace Collection: Statistics

Modelling the Association and Prediction of Cardiovascular Disease Using Log-linear and Binary Logistic Regression Approaches.

Sat, 04 Apr 2026 00:00:00 GMT

Title: Modelling the Association and Prediction of Cardiovascular Disease Using Log-linear and Binary Logistic Regression Approaches. Authors: Aliyu, Otori Iliya; Adetutu, Olayiwola Matthew Abstract: Cardiovascular diseases are group of disorders of the heart and blood vessels that constitute the leading cause of death globally. This research focused on determining the factors associated with the likelihood of developing cardiovascular disease, and examining the pattern of association and interaction among categorical variables responsible for cardiovascular disease in Northwestern Nigeria. Data on cardiovascular risk factors and symptoms from a cohort comprising healthcare personnel and patients over a period extending from August 15, 2024 to September 15, 2024 were collected. Risk factors admitted by respondents including High Blood Pressure (Hypertension) acknowledged by 21.1% of respondents, High Cholesterol recognized by 15.2% of participants, Smoking practiced by 12.4% of the cohort, Alcohol Consumption reported by 8.2% of respondents, Unhealthy Diet admitted by 11.8% of participants, Physical Inactivity identified by 12.1% of the study population, Obesity and Overweight prevalent in 10.3% of respondents, and Diabetes recognized by 8.8% of the cohort which provided valuable intuitions into the prevalence of risk factors in the Northwestern Nigerian context. Findings from logistic regression affirmed age, gender, diagnosis, symptoms, risk factors, and family history as significant predictors of cardiovascular diseases with p-values 0.000, 0.000, 0.004, 0.000, 0.000, 0.002, and 0.001 respectively. Log linear modelling revealed positive partial association between age and gender, gender and residing site, age, gender, residing site with cardiovascular disease with p-values 0.0000, 0.0000, 0.0000, 0.0000, 0.0000 and 0.0000 respectively, while age and residing site with 0.0640 was not impactful. Description: This study investigated factors associated with cardiovascular diseases (CVDs) and the patterns of association among categorical variables in Northwestern Nigeria using data collected between August 15 and September 15, 2024. Hypertension (21.1%), high cholesterol (15.2%), physical inactivity (12.1%), unhealthy diet (11.8%), and smoking (12.4%) were prominent reported cardiovascular risk factors. Logistic regression identified age, gender, diagnosis, symptoms, risk factors, and family history as significant predictors of cardiovascular diseases (p < 0.05). Log-linear analysis revealed significant associations among selected demographic variables and cardiovascular disease, highlighting the importance of understanding interactions among categorical risk factors.

Spatial Analysis and Hotspot Detection of Firearm Data Reported in Abuja, Nigeria

Mon, 30 Mar 2026 00:00:00 GMT

Title: Spatial Analysis and Hotspot Detection of Firearm Data Reported in Abuja, Nigeria Authors: Abdullahi, U.; Musa, Y. M.; Adeyemi, R. A.; Oguche, S. M.; Abdullahi, I. M. Abstract: The increased availability of crime data in the Federal Capital Territory (FCT), Abuja, has made firearms a major topic of debate and research. Improving the understanding of the factors that contribute to gun violence in Abuja is critical to law enforcement to abate violent crime. This study conducted a spatial analysis of firearm and crime management and other pertinent factors reported cases across FCT, Abuja, from 2020 to 2024. Applying data sourced from the Nigeria Police Force Headquarters, FCT command Abuja, the National Bureau of Statistics (NBS), and reports from Non-Governmental Organizations (NGOs), the study examined the presence of spatial autocorrelation, determine whether firearm occurrences were statistically dependent on their geographic location, and detected statistically significant clusters of illegal firearm possession and recoveries over time using hotspot mapping methods. The result showed that FCT has an average of 2.80 firearm possession per theft involving a firearm. The result also revealed that firearm recoveries are close to where they were illegally possessed. Locally Made Guns (LMGs) were illegally possessed more than any other type of firearm and were more commonly used in the commission of crime in FCT. Furthermore, results from hotspot analyses of crime over time revealed that crime clustering varies dramatically from year to year. This research recommended that crime cases should be recorded in detail alongside geographical coordinates of the crime incidence spot so as to allow hotspot analysis at the spot level rather than the street level Description: Crime Hot-spot mapping of Fire arms

Bayesian Geo-Additive Modelling of State-Level Heterogeneity in Anaemia Prevalence and Risk Factors among Under-Five Children in Nigeria

Tue, 01 Oct 2024 00:00:00 GMT

Title: Bayesian Geo-Additive Modelling of State-Level Heterogeneity in Anaemia Prevalence and Risk Factors among Under-Five Children in Nigeria Authors: Aminu, Ibrahim; Adeyemi, R. A.; Usman, A.; Musa, A. O Abstract: Anemia is a very serious global health issue, particularly in sub-Saharan African countries, where it has significant implications for both human health and economic development. This study aims to identify the socioeconomic, demographic and climatic factors as well as geographical variations linked to the prevalence of anaemia in young children in Nigeria, based on the results of the 2018 Nigeria demographic and health survey. The association between various types of covariates and possible spatial variations was explored using a hierarchical Bayesian geo-additive modelling approach. In particular, the study focused on a binary response variable. Out of the four formulated semi-parametric models, geo-additive model with both structured and unstructured random effects was found to be the best fitted. The findings of the study reveal significant spatial variation in anemia risk, with the highest risk observed in the states of Sokoto, Niger, Akwa Ibom, Ebonyi and Bauchi. Besides, educational level of a child’s mother, wealth status of household, a child’s area of residence, prevalence of malaria and land surface temperature were all associated with childhood anemia. The prevalence of infant anemia decreased with increasing child's age. Mother’s Body Mass Index also has inverse relationship with the risk of childhood anaemia. Given the observed state-level patterns of anemia risk, it is important to implement targeted programs that address the specific needs of vulnerable children in each state. Th is could help reduce the prevalence of childhood anemia in the Nigeria Description: Bayesian Geo-Spatial modeling childhood anaemia in Nigeria

Shared Component Model for Childhood Anaemia, Diarrhoea, and Fever Comorbidities in Nigeria: A Geospatial Perspective

Wed, 01 Jan 2025 00:00:00 GMT

Title: Shared Component Model for Childhood Anaemia, Diarrhoea, and Fever Comorbidities in Nigeria: A Geospatial Perspective Authors: Aminu, Ibrahim; Adeyemi, R. A.; Usman, Abubakar; Raji, Mohammed; Bashiru, Sule O.; Isaac, Adaji; Musa, Aisha O. Abstract: Children under the age of five in Nigeria continue to experience significant comorbidities of diseases, contributing to high morbidity and mortality rates. This study applied a Bayesian shared component model to separate the specific and shared risk factors associated with anaemia, diarrhoea, and fever among children across the states in Nigeria. Regional climatic variations were integrated into the spatial modelling framework to enhance the analysis. Childhood disease data were sourced from the 2018 Nigeria Demographic and Health Survey. The identified risk factors common to the three health conditions are wealth index of household, maternal educational level, land surface tempera-ture and regional precipitation. Geospatial analysis of the posterior disease risk estimates revealed that the comorbidities of anae-mia-diarrhoea, anaemia-fever, diarrhoea-fever, and anaemia-diarrhoea-fever are disproportionately higher in the northeastern and southern re-gions of the country. To significantly mitigate the risk of disease comorbidities, policymakers and health authorities in Nigeria should im-plement initiatives to address common risk factors, with priority given to the identified hotspot regions. Description: Disease Co-morbidity (anaemia, diarrhoea, and fever) among under five children in Nigeria: A Geo-spatial modelling