Housing determinants were measured by indicators as follows: housing density index, ventilation index, and indoor air pollution number. Social class was specified by productive assets ownership of respondents (i.e., having no productive assets, having one productive asset, and having more than one productive asset). Per capita income was indicated by per capita income for Lampung Province in 2016 with exchange rate IDR 12,000 for US $1 (i.e., poor sufficient: US $2,989). Occupation was the employment status of respondents in the last 12 months (i.e., unemployed, temporary employee, and permanent employee). Education was indicated by period that the respondents had been spent for their formal education (i.e., uneducated: 12 years). Socioeconomic position determinants were measured by the following indicators: education, occupation, per capita income, and social class. Smear-positive TB of a family member, neighbors, and employees, recording from previous period, was used as an evident of those related transmissions. Meanwhile, working environment transmission was a transmission from employees who worked in the same workplace. Surrounding house transmission was a transmission from neighbors who lived surrounding the respondents. Internal house transmission was a transmission from family members of the respondent who lived in the same house. TB transmission was measured by indicators: internal house transmission, surrounding house transmission, and working environment transmission. Using dichotomous variables based on theoretical cutoffs, we can build model regarding to both ideal and nonideal condition. In this research, variables were measured in dichotomous rather than continuous. The independent latent variables included socioeconomic position determinants and TB risk factor determinants (housing, nutritional, and health access). The dependent latent variable was TB transmission. The research variables consisted of independent latent variables, dependent latent variables, and their indicators. The sampling technique in this research was simple random sampling. This study used a sample of 166 smear-positive TB patients, which was the minimum sample size calculated using 80% power and 95% confidence intervals. Population in this study was all patients with smear-positive TB from January to June 2017 recorded in 30 community health centers (CHCs) that implemented the DOTS strategy, consisted of 635 smear-positive TB patients. The results of this model confirmed which determinants and which indicators should be considered as a basis for a suitable intervention strategy to decrease TB transmission.Ī cross-sectional study was conducted in Bandar Lampung from January to November 2017. By using the PLS method, both the determinants that significantly influence TB transmission and the indicators that best identify those determinants can be identified. Since these determinants are latent variables, the partial least square (PLS) method was used to develop a model. The research aims to develop a prediction model of TB transmission based on socioeconomic position determinants and TB's risk factors determinants.
Therefore, knowledge of how socioeconomic position and TB risk factors influence TB transmission is required to support TB control program to decrease TB incidence. Moreover, research also showed that clustered TB incidences were located in the area of Bandar Lampung with low-socioeconomic position. The research showed that individual with low-socioeconomic position would have higher TB risk factors which then influenced to develop TB. In addition, recent studies in Bandar Lampung showed that socioeconomic position in individual and community have potential role to TB incidence. The risk of transmission is higher for people with lower socioeconomic position compared to people with the higher socioeconomic position. Studies have shown that disease transmission or contact occurs from inside the house, surrounding homes, and the working environment.
The increasing of TB cases suggests that there are disease transmissions or contacts among closely related people in the community. It is also well known that TB is highly correlated with poverty level. Moreover, Bandar Lampung is located in the fifth poorest province in Indonesia. Bandar Lampung has been recorded as one of the cities, in Indonesia, with a high rate of TB incidence, and with 2056 cases in 2016 compared to the 1,195 cases in the year 2012. The number of incidences in 2016 was about twice the number in 2012.
Indonesia has also struggled with an escalation of the rate of TB incidence. Indonesia is a country with the third highest rate of tuberculosis (TB) incidence in the world.