<![CDATA[Pulmonary tuberculosis (TB) with positive Acid-Fast Bacilli (AFB+) remains one of the most transmissible infectious diseases worldwide. This disease poses a significant public health challenge in many countries. This study aimed to develop a risk-factor-based intervention model to reduce the incidence of Pulmonary TB (AFB+). A case-control approach was employed, with the case group comprising people diagnosed with Pulmonary TB (AFB+), and the control group consisting of non-TB individuals from the same neighborhoods. Binary logistic regression was used for bivariate analysis, and multivariate analysis utilized logistic regression. This study found that the social determinants model accounted for 34.9% of the variance in the incidence of Pulmonary TB (AFB+) (R² = 0.349). The biological determinants model showed an R² of 0.127, indicating that this model explains 12.7% of the variance in the disease. The third model, which focused on behavioral determinants, had an R² of 0.312, meaning that behavioral factors accounted for 31.2% of the variance. The fourth model, examining the physical condition of housing, showed an R² of 0.425, indicating that 42.5% of the variance in Pulmonary TB (AFB+) is explained by variables related to housing conditions. In conclusion, the physical condition of housing emerged as the strongest predictor of Pulmonary TB (AFB+). These findings suggest that improving housing conditions should be a key component of public health strategies to reduce the incidence of Pulmonary TB (AFB+). Targeted interventions to improve the household environment are crucial for reducing the risk and transmission of Pulmonary TB (AFB+).]]>
Copyrights © 2025
