Risk Prediction Model of Lung Tuberculosis Using Spatial Approach in the Coastal Area of Makassar City Rahman Stang Abdul1,*, Salmah A. Ummu1, Dwinata Indra2, Mallongi Anwar3 1Department of Biostatistics, Hasanuddin University 2Department of Epidemiology, Hasanuddin University 3Department of Environmental Health, Faculty of Public Health, Hasanuddin University *Corresponding Author: Stang Abdul Rahman, Department of Biostatistics, Faculty of Public Health, Hasanuddin University, Mobile: 08529836701, Email: stangbios@gmail.com
Online published on 21 February, 2019. Abstract This type of research is an analytic observational study using the case control method, to study the distribution area of the occurrence of pulmonary tuberculosis with spatial epidemiology approach and establish a prediction model for the incidence of pulmonary tuberculosis using a spatial approach. A sample of 236 people consisting of 118 cases and 118 conferences. Case samples were positive smear pulmonary tuberculosis patients and as controls not pulmonary tuberculosis patients who were recorded in TB form 03 tribes I, II, III and IV in 2017 Makassar City and lived in the coastal area of Makassar City (Tallo District). The results showed that spread of pulmonary tuberculosis cases in the coastal areas of Makassar City was correlated with population density in an area, total socioeconomic status and contact history of patients and did not correlate with the distance of health services namely health centers. Variables of family economic status, smoking status and contact history with pulmonary tuberculosis sufferers are significant in predicting the risk of pulmonary TB incidence in the coastal area of Makassar City. The prediction model for the incidence of pulmonary TB in the coastal areas of Makassar City is: Ln (p/(p-1)) =-0.976 + 0.854 social status + 0.660 smoking status + 2.801 contact history Further research is needed on the intervention model for the prevention of the incidence of pulmonary tuberculosis in the coastal areas of Makassar City in collaboration with economists, nutrition and the environment. Top Keywords Lung Tuberculosis, Spatial, Model. Top |