Factors Associated with Knowledge, Attitudes, and Practices about Tuberculosis in Peruvians
Joan A. Loayza-Castro, Luisa Erika Milagros Vásquez-Romero, Verónica Eliana Rubín-de-Celis Massa, Cori Raquel Iturregui Paucar, Norka Rocío Guillén-Ponce, Sonia Indacochea-Cáceda, Jenny Raquel Torres-Malca
International Journal of Statistics in Medical Research · 2023-06
Abstract
Objective: To determine the factors associated with knowledge, attitudes, and practices (KAPs) about tuberculosis (TB) in the Peruvian population. Materials and Methods: A cross-sectional, analytical study was carried out by conducting a virtual survey. The instrument that was used consisted of 4 sections: sociodemographic variables (9 questions), knowledge (23 questions), attitudes (9 questions), and practices (8 questions) about tuberculosis. Univariate and bivariate analyses and the Poisson regression model with robust variance were used to obtain crude and adjusted prevalence ratios (PRa). Results: The sample consisted of 1284 participants. Regarding knowledge, attitudes, and practices about TB, an insufficient level was found in 47.97%, 50.3%, and 54.36% of the cases, respectively. The variables that increased the probability of having sufficient knowledge were sex, grade, area, family history, and history of having TB. While only the area and both antecedents were for attitudes. Finally, the age, degree, and history of TB were for the practices. Conclusion: There are insufficient KAPs in around half of the population studied. In addition, there are differences according to the epidemiological characteristics, such as sex, age, academic degree, area, and family history of TB and having had this disease. Therefore, the importance of research in this field should be emphasized in the face of a disease that is related to the differences in the levels of these variables between different strata of the general population.
MeSH terms
- Bivariate analysis
- Family history
- Poisson regression
- Tuberculosis
- Univariate
- Population
- Epidemiology
- Medicine
- Demography
- Disease
- Environmental health
- Family medicine
- Multivariate statistics
- Statistics