Modelling the associated risk factors of urinary tract infections (UTI) Using Logistic Regression - Victor-Edema, Uyodhu Amekauma; Njigwum, Allwell Sunny; Amadi-Wali, Owhorchukwu (Faculty of Natural and Applied Sciences Journal of Mathematical and Statistical Computing, 2023)
The lack of knowledge and improper awareness of the potential risks of urinary tract infection (UTI) is one of the major factors accounting for its high prevalence rates in Nigeria. This study aims to identify risk factors associated with urinary tract infections using logistic regression in tertiary health facilities in Rivers State. The study adopted a case-control observational design using retrospective data. The study population included the data of patients visiting Rivers State University Teaching Hospital from 2021 to 2023. The sample size was determined by using the 43.7% prevalence rate of UTI in the country with the aid of the Scalex SP calculator. A sample size of 592 patients was utilized for the study, and a purposive sampling technique was used to draw data from the records of patients screened for UTI. Data collected was analyzed using univariate (descriptive), bivariate (Chi-square) and multivariate (binary logistic regression) statistics. The SPSS version 27 was utilized for the statistical analysis. The result showed that urinary tract infections had an overall prevalence of 24.8%. Also, it was revealed that age is significantly associated with urinary tract infections, while gender is not. Finally, the sociodemographic factors (age and sex) significantly predict urinary tract infections among patients. Specifically, middle-aged persons (50-59yrs) were 7.6 times more likely to have UTI compared to children and teens (0-17yrs) (95% CI 2.12, 27.27). Finally, it was recommended that special care should be given to age groups who are at higher risk of contracting urinary tract infections.