KAJIAN DETERMINAN SOSIAL KEJADIAN TUBERKULOSIS PARU BERBASIS GEOSPASIAL DAN MODEL PREDIKSINYA DI BANDAR LAMPUNG

Abstract

TB Background: TB control program has been successful in increasing the cure rate and saved many lives, but less successful in reducing the incidence, especially in thirteen countries with high TB incidence, including Indonesia. Therefore, TB control will move \"out of the box TB\" with emphasis on the social determinants. In Bandar Lampung, the incidence of TB has been increasing, although its cure rate has been reaching above 85%. Bandar Lampung also has low social determinants and low TB�s risk factors indicators. Objectives of this research are to provide a prediction model of social determinants and TB incidence as well as to study spatial analysis of social determinants and TB incidence. as case group Methods: The research was conducted at 27 primary health centers and one hospital that have implemented DOTS strategy in Bandar Lampung. Population of the research consisted of all patients with smear-positive TB that was recorded in the health services during January to July 2012 with total of 628 people. In the first subtopic, sample consisted of 238 cases of smear-positive TB patients and 238 TB suspects who have been diagnosed without TB as control group. Variables of the first subtopic of this research are social determinants, housing conditions, household food security, access to health service and incidence of TB. In the second sub-topic, sample consisted of 628 patients with smear-positive TB. Variable in this sub-topic consisted of the geographical coordinates of patients with TB, population density and proportion of poor households. Analysis of this research consisted of Structural Equation Modeling with Partial Least Square method, SaTScan and Geoda 0.95-i (Beta). : Results: The result shows that the social determinants affect TB incidence through housing conditions and household food security with equation TB incidence = 0,266* housing condition + 0,094* social determinants + 0,328* household food security + 0,067* health access and R 2 = 34.15%. Spatial analysis proved that although there is no spatial relationship between population density and the proportion of poor household of TB incidence, but the distribution and clustering of TB has been occurred in areas with high number of both population density and proportion of poor household. Conclusions: Social determinants indirectly influence the TB incidence through housing conditions and food safety. Therefore, it is required a DOTS program that supported by improvement efforts of the social determinants that will be able to improve housing conditions and food safety. The program should be supported by other health related sectors and other sectors