Determinants of Tuberculosis Infection in Diabetic Patients: A Cross-Sectional Analysis of Socio-Demographic, And Risk Factors at Kapsabet County Referral Hospital, Nandi County Kenya

Abstract

The co-infection of Tuberculosis (TB) and Diabetes Mellitus (DM) presents a critical public health challenge, especially within low-resource settings where healthcare systems struggle with limited resources. Diabetic patients are at heightened risk of developing TB, yet factors influencing TB infection within this population are not thoroughly understood. This study investigates the prevalence and determinants of TB infection among diabetic patients at Kapsabet County Referral Hospital. The research addresses gaps inknowledge regarding how socio-demographic, individual, and environmental factors interact to influence TB susceptibility among this vulnerable group. Employing a descriptive cross-sectional design, data were collected from 60 diabetic patients selected through a simple random sampling technique. Data were obtained via structured questionnaires, patient interviews, and medical record reviews. Statistical analysis included descriptive statistics, Chi-square tests, and ANOVA to explore associations between TB infection status and various predictors. The sample’s socio-demographic characteristics and diabetes-related variables were analysed using SPSS, with significant relationships identified at a p-value of <0.05. Results revealed a TB prevalence rate of 16.7% for active cases and 8.3% for latent infections among diabetic patients. The Chi-square analysis indicated that lower education levels (p = 0.031) and lower income brackets (p = 0.024) were significantly associated with TB infection status. Additionally, individual factors, including Type 2 diabetes (p = 0.014) and poor glycaemic control (p = 0.022), were identified as significant predictors of TB risk. ANOVA results further demonstrated that patients residing in overcrowded environments exhibited highermean TB infection rates compared to those in less crowded conditions, F (2,57) = 5.26, p = 0.009. Frequent exposure to known TB cases was also significantly associated with infection status (p = 0.015). In conclusion, this study highlights a substantialburden of TB-DM co-infection within the study population, with socio-demographic, individual, and environmental factors significantly influencing TB risk. The findings underscore the need for integrated TB and diabetes management strategies that consider socio-economic and environmental conditions. Targeted interventions focusing on improving diabetes care, enhancing patient education, and reducing exposure to environmental risk factors are recommended to mitigate TB risk among diabetic patients.