Indeed, studying this certain aspect of the relationship between regimen type and health is critical not only to general science, but to our understanding of how to improve health care systems of countries and health outcomes of populations. This thesis will examine some of the ways in which the difference in regime type plays out, particularly in relation to health and health outcomes. I will also relate the discussion of the literature and the results to the experiences of Chile, the location of my study abroad experience.
They defined public goods as goods that benefit all members of the population equally (such as clean air and national defense), while private goods specifically benefit those to whom the good is given (defense contracts and corruption payments, for example). He analyzed the use of the public health care system by uneducated mothers and birth data from the period around the change to EV. Before moving on to the methodology, tests and analysis of the hypothesis, this investigation could nevertheless benefit from being rooted in the story of one particular.
According to the authors, the duality of the system has created several effects, including negative effects on income inequality and inequitable access to quality health providers for those in the public system. Ultimately, Pinochet and the democratic governments under Alywin, Frei and Lagos that followed acted fundamentally differently because of the. First, my dataset contains data for almost all of the 191 countries listed in the Freedom House report for 2008.
Each of these indicators measures the character of a different part of the health care system: its efficiency (IMR), government and private investment (HCS), and its depth and penetration (PD). It comes from the World Health Organization, which defines it as the "number of doctors relative to the size of the population." Accordingly, the scale is in doctors per 1000 population. The scale of the indicator is from 1-7, with 1 indicating the most free and 7 indicating the least free.
My second competing independent variable is the Absolute Value of the Latitude of each country's capital city. This is simply a measure of the relative distance of each country's capital from the equator, and the scale is in degrees, measured in a. This indicator was chosen to provide an indication of the effect of conflict on health care.
The data comes from the World Bank, which adds: “Net official development assistance (ODA) per capita consists of concessional loan disbursements (excluding principal repayments) and grants from official agencies. I rate each of my variables according to their statistical significance, and the level of significance is indicated by asterisks next to the coefficient; one asterisk (*) indicates statistical significance (p is less than 1%), while three (***) indicates a highly significant result (p is less than 0.1%). Finally, the correlation coefficient is important: the coefficient shows the extent and direction of the influence of the independent variable on the dependent variable.
A coefficient of 2 means that for every one-unit increase in the independent variable, there is a two-unit increase in the dependent variable.
Results and Analysis
The value of R2 is quite high, which means that the model fits the reality of the data quite well. Second, several other variables, particularly latitude and rural population, are much more statistically significant for the change in the dependent variable; these contradict my second hypothesis as they are more important than FHR. Finally, it is interesting to note that GDP per capita and ODA, both monetary variables, were not statistically relevant predictors of IMR.
Three of the independent variables have significant multiple-regression coefficients: Freedom House scores, Latitude and. This may simply be a reflection of the fact that European countries, which spend a lot on health care, are all at fairly high latitudes: the fact that latitude consistently comes up so significantly in all the tests is noteworthy. It should be noted that the R2 value for this test is extremely high, at .668, especially considering that it is in the field of political science.
First, FHR, the Main Independent Variable, was not significantly correlated with PD, the indicator of the depth and pervasiveness of the health care system. Secondly, the GDP shows here as highly significant; in the other two indicators it had no significant correlation. This is an interesting result: although GDP did not play a role in influencing health care outcomes, it does influence the depth and pervasiveness of the system.
The results of the three regression analyzes taken together, as hoped, have clear implications for the hypothesis put forward earlier in this article. For two of the three health-related dependent variables, the statistical test is clear that there is a significant relationship. Rural population also correlates with two of the three health indicators, and surprisingly, latitude was the only factor that was significant in all three variables.
These variables tend to be more a measure of the conditions under which people live rather than government action. As can be clearly seen in the graph, the infant mortality rate falls much faster under Pinochet's regime compared to the following democratic one. Regime type appears to be a factor: around the time of the transition to democracy, IMR began a noticeable decline after several years of stagnation.
Conclusions
This result is extremely surprising: given the impact wealth is expected to have on health care, the absence of a significant relationship between this and both infant mortality rate and the money spent on health care is in the face of the way one would expect the world to work. Further research will be needed to confirm and put these findings into perspective and this result is by no means definitive, but it could lead to an interesting dialogue about the importance of wealth in health care. These results logically lead to new perspectives on improving health care on a global scale.
Democracies have long been noted to correlate with many positive indicators such as higher GDP, but their statistically significant relationship with healthcare-related factors such as infant mortality and healthcare spending adds another benefit to improving political freedoms and civil rights. However, the fact that environmental variables such as latitude and percentage of rural population are more statistically relevant leads to the logical conclusion that efforts to improve the ecological and infrastructural conditions in which people live, such as combating tropical diseases and increasing access to clean water sources, will improve health care more effectively than giving foreign aid or inducing regime change. Although democracies have higher levels of social spending and are more responsive to citizen demands, other factors, such as improving the conditions in which people live, are more important to improving health care.
If democracy is a statistically significant predictor of better health care systems, then one would expect that democratization in the region would lead to better health for citizens. In a region that has routinely witnessed undemocratic governance of all kinds, from military dictatorships to semi-authoritarian states with non-competitive elections, this is one more reason to call for the development and real protection of political rights and civil liberties. . Second, because the most significant results of this analysis were those that measured, among other things, the natural and infrastructural environment in which people live, this study confirms that large gains in health care can be achieved even without changing the type of regime. of countries.
Low-cost but effective efforts to combat tropical diseases and increase access to infrastructure, two elements of the latitude and rural population indicators, can be achieved without regime change (even though democratic governments would theoretically prioritize these goals ). Finally, the monetary variables were generally less significant than the regime type and environmental variables. A direct application of this would be a greater emphasis on U.S. policies that focus on directly helping build infrastructure and increasing access to health care, rather than providing non-specific aid to poorer countries.
Works Cited
Decentralization, Democratization, and Liberalization: A History of Revenue Sharing in Argentina Journal of Latin American Studies. Democracy, Authoritarianism, Political Conflict, and Population Health: A Global, Comparative, and Historical Approach.” Social Science and Medicine. Review Article: Politics, Welfare Regimes and Population Health: Controversies and Evidence.” Sociology of Health and Illness.
