Longitudinal clustering of tuberculosis incidence and predictors for the time profiles: the impact of HIV
OBJECTIVES: To identify longitudinal trends in TB incidence in Portugal from 2002 to 2012 and investigate the longitudinal effect of sociodemographic and health-related predictors among the resident population on the TB incidence rate.
METHODS: We used data from the National Tuberculosis Surveillance System and other national institutions. K-means longitudinal clustering algorithm was performed on TB incidence time profiles from districts of Portugal.
RESULTS: Three longitudinal profiles for the TB incidence rate of Portugal were identified. In all of them, TB incidence decreased over time. Among all studied sociodemographic and health-related predictors, human immunodeficiency virus (HIV) notification rate and unemployment were shown to have (positive) significant effects on TB incidence. In particular, the greatest effects were found for the HIV notification rate.
CONCLUSIONS: Our study supports the view that combined TB-HIV strategies and the improvement of social determinants can contribute to decreases in TB incidence.
Keywords: AIDS; human immunodeficiency virus; public health; tuberculosis; unemployment
Document Type: Research Article
Affiliations: 1: Faculty of Medicine of Porto University, Porto, Portugal 2: Centre of Mathematics, University of Porto, Porto, Portugal; School of Allied Health Sciences, Polytechnic Institute of Porto, Vila Nova de Gaia, Portugal 3: Epidemiology Research Unit Institute of Public Health, University of Porto, Porto, Portugal; Centro Hospitalar de Vila Nova de Gaia/Espinho EPE, Vila Nova de Gaia, Portugal 4: Centre of Mathematics, University of Porto, Porto, Portugal; Mathematics Department, Faculty of Sciences, University of Porto, Porto, Portugal 5: Epidemiology Research Unit Institute of Public Health, University of Porto, Porto, Portugal; Centro Hospitalar de Vila Nova de Gaia/Espinho EPE, Vila Nova de Gaia, Portugal; Chest Disease Centre, Vila Nova de Gaia, Portugal; Department of Clinical Epidemiology, Predictive Medicine and Public Health, University of Porto Medical School, Porto, Portugal
Publication date: 01 August 2016
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