Macroeconomic Factors On The Number Of Pulmonary Tuberculosis Patients In North Sumatera

The Unit Root Test

The result of the study begin with checking the stationarity of the data becausethe variables should be stationary before using the error correction method (ECM). The null hypothesis of the unit root test is generally defined as the presence of a unit root and the alternative hypothesis is stationary. The unit root test used in this study is the Phillips–Perron (PP) test. The result of this test in level shown by Table 1 .

Table 1 . shows that none of the variables stationary in level.This is means that it must be proceed with the next level such as the first difference or the second difference until the result of the unit root test shows that the variables stationary. The result of the unit root test in the first difference shown by Table 2

The result of Phillips-Perron unit root test in the first difference shown by Table 2 basically suggest that finally the variables stationary in the first difference. It is shown by the probability of t-statistics lower than the critical value 0.05. Based on this findings the next test, that is the cointegration test can be proceed because the requirement of stationary variables is fullfilled.

The Result of Cointegration Test

This study used a cointegration Engle-Granger (EG) test. The test conducted on the residual of the equation of multiple linear regression to decide their stationary. The decisions based on the comparison of the ADF statistic to the critical value α = 0.05. If the statistics are greater than the critical value, it can be concluded the the variables observe are cointegrated or having a long-term relationship. If otherwise the statistics not greater than critical value, then the variables are not cointegrated. Judging from the estimated value of -5.613989 ADF statistic greater than critical value α = 5% (-3.119910) and the probability 0.0008 <α = 0.05, so it is can be concluded that they are cointegrated. This result shown by Table 3

The Result of Estimation Model

The result of ECM model is:

dLnTBt=1.2295+6.4689*dLnINFt–0.3053*dLnEDUt+ 0.4922*dLnPOVt+1.4269*dLnPOPt-20.1088*dLnHFt– 1.7612*ECT

The complete result of estimation model such as the F-statistics, R-squared, the coefficient of each variable, t-statistics and its probability shown by Table 4 .

The results of the estimation of the model shown by Table 4 indicates that all the variables studied in the short term affect significantly the number of tuberculosis patients in Medan. Inflation variable positively and significantly affected the number of patients of pulmonary tuberculosis. Variable education, negatively and significantly affected the number of patients. While variable poverty also found positively and significantly influence the number of patients of pulmonary tuberculosis. Similarly, the number of population has a significant effect on the number of patients with pulmonary tuberculosis, whereas the variable number of health facilities also significantly influence the number of patient but in a negative relationship.

Inflation variables found to affect positively and significantly the number of tuberculosis patients in Medan. The term inflation in this study is a persistent, ongoing rise across a broad spectrum of prices, not just one or two goods but that increase is spreads to (or leads to escalating prices for) other goods. The measurement of inflation in Indonesia based on the consumer price index, especially food stuffs, housing, clothing and health. Inflation as macroeconomic indicators caused lower ability to fulfill the nutrition needs. Nutritional deficiencies will lead to susceptibility to tuberculosis as studid by Chandra (1997) and Cegielski and McMurray (2004). This means that the higher the rate of inflation will increase the number of tuberculosis patients in North Sumatera.

Variable education found affected negatively and significantly the number of patients with pulmonary tuberculosis. This means that the higher the educational level the less the number of patients with pulmonary tuberculosis. This can be explained by the study Ross and Wu Chia-ling (1995) which states that people who have higher education have a greater control to their ill-health and always promote health in all their analysis. This finding is consistent with studies Gupta, Das, Balamughesh, Aggarwal, & Jindal, (2004) that education negatively affect the number of patients with pulmonary tuberculosis.

Number of health facilities in the current study found significantly and negatively affected the number of pulmonary TB patients in North Sumatera. This is means that the higher the number of health facilities the lower the number of TB patients. Adequate health facilities will facilitate the efforts of TB preventive and treatment efforts. Assessment of the WHO (2010), Golub et al. (2007) and Lin, Murray, Cohen, Colijn, & Ezzati, (2008) showed problems of health systems and health facilities in dealing with pulmonary TB will increase the number of TB cases very quickly.

The results of this study also indicated that poverty is the most influential variables on the number of patients with pulmonary tuberculosis in North Sumatra. This is because poverty is a big barrier to get healthy food, to get the immune system that can prevent infection of pulmonary tuberculosis. Poverty is also a barrier to get a decent place to stay with normal ventilation system to maintain health. Poverty is also a barrier to getting health efforts if someone gets sick, and poverty can also be a cause of disease transmission. Studies on poor countries and poor people (Lönnroth, Jaramillo, Williams, Dye, & Raviglione, 2009 and Muniyandi et al., 2007) showed that they are more prone to this disease compared to people in middle income countries.

The number of population in this study found to be the second important variable that influence the number of pulmonary TB patient after variable the number of poverty. This is due to the explosion of the population will affect the availability of food, shelter and other health needs. High population tend to cause a shortage of the important things. High population means a high number of dependents for the heads of households, leading to work hard in a poor working environment. Transmission of TB will be higher in the family if there are higher number of family members. The results of this study is in line with previous studies such as the reviews by Dye and Williams (2010) or studied by Narasimhan, Wood, MacIntyre, & Mathai, (2013).

Finally, it can be said that the proposed macroeconomic variables studied in this paper found significantly influence and play a significant role in increasing or reducing the number of patients with pulmonary tuberculosis in North Sumatra. Other variables such as the level of air pollution, urbanization conditions that are common in big cities, followed by dense and bad settlements, that are not included in this study is expected to also affect the number of TB patients in North Sumatra. All of the proposed factors in this study basically are not merely a health problem, but also economic, social inequality and poverty. This is the same as stated by van Helden (2003) in his study of TB disease, he states that tuberculosis is not just a medical problem, but also a problem of social inequality and poverty and it is always the result of gross defects in socialorganization and in thenmanagement of individual lives.It is truly a social sin which canand must be stamped out.