Data from: Tuberculosis research in road construction sites

Introduction: Workers with occupational exposure to respirable silica dust like casual labourers at road construction sites (RCSs) are known to be at a high risk of developing pulmonary tuberculosis (TB). There is limited literature about the burden of PTB among this sub-population with high occupational exposures to silica dust at road construction sites. We aimed to determine the prevalence of PTB among casual labourers working at road construction sites in Central Uganda. Methods: We enrolled 297 participants by consecutive sampling into a cross-sectional study in September 2022 at four road construction sites in four districts in Central Uganda. A structured questionnaire was administered and the PTB cases were identified using a Gene Xpert and/or Computer Aided Detection for TB (CAD4TB). Data were analyzed in STATA version 17.0. Descriptive statistics adjusted for clustering were used to summarize the data and the relationship between PTB and independent variables were assessed using a mixed effects modified Poisson regression model to estimate the adjusted prevalence ratios. Results: Most participants were males (95.6% (284/297)), median age was 29 years [Interquartile range (IQR); 25, 33]. The prevalence of PTB among casual labourers was 2.4% (95% CI: 1.9, 2.8). Being vaccinated with BCG (3.45, 95% CI (1.02, 11.61)), alcohol use (2.70, 95% CI (1.52, 4.80)) and staying in overcrowded house (8.13, 95% CI (4.37, 15.12)) were positively associated with having PTB.s Conclusion: There is a high prevalence of PTB among casual labourers working at road construction sites in Central Uganda. Individuals who had never been vaccinated with BCG, alcohol users and those staying in overcrowded houses were at an increased risk of having PTB. We recommend routine screening of casual labourers at road construction sites to optimize active TB case finding. An approved questionnaire was administered to all study participants. Data entry was then done of filled questionnaires using Epidata, upon a finishing completeness check. The soft copy data was then extracted into STATA17 for cleaning and analysis. # Data from: Tuberculosis research in road construction sites [doi.org](doi.org) Generally, the dataset has variables derived from study participants' socio-demographic characteristics, clinical characteristics and Laboratory results all of which are clearly explained in the attached data dictionary. ## Description of the data and file structure The TB result is derived from a concatenation of a CXR result, MTB result, and the RIF status which abbreviations have been clearly explained in the data dictionary. Missing values are denoted by NA The variable age was categorized into three groups with codes 1,2 and 3 that is 19/28=1, 29/35=2, 36/52=3